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Li N, Li YL, Li LT. Development and validation of a nomogram predictive model for cerebral small vessel disease: a comprehensive retrospective analysis. Front Neurol 2024; 14:1340492. [PMID: 38259650 PMCID: PMC10801164 DOI: 10.3389/fneur.2023.1340492] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2023] [Accepted: 12/19/2023] [Indexed: 01/24/2024] Open
Abstract
Background Cerebral small vessel disease (CSVD) is a significant contributor to stroke, intracerebral hemorrhages, and vascular dementia, particularly in the elderly. Early diagnosis remains challenging. This study aimed to develop and validate a novel nomogram for the early diagnosis of cerebral small vessel disease (CSVD). We focused on integrating cerebrovascular risk factors and blood biochemical markers to identify individuals at high risk of CSVD, thus enabling early intervention. Methods In a retrospective study conducted at the neurology department of the Affiliated Hospital of Hebei University from January 2020 to June 2022, 587 patients were enrolled. The patients were randomly divided into a training set (70%, n = 412) and a validation set (30%, n = 175). The nomogram was developed using multivariable logistic regression analysis, with variables selected through the Least Absolute Shrinkage and Selection Operator (LASSO) technique. The performance of the nomogram was evaluated based on the area under the receiver operating characteristic curve (AUC-ROC), calibration plots, and decision curve analysis (DCA). Results Out of 88 analyzed biomarkers, 32 showed significant differences between the CSVD and non-CSVD groups. The LASSO regression identified 12 significant indicators, with nine being independent clinical predictors of CSVD. The AUC-ROC values of the nomogram were 0.849 (95% CI: 0.821-0.894) in the training set and 0.863 (95% CI: 0.810-0.917) in the validation set, indicating excellent discriminative ability. Calibration plots demonstrated good agreement between predicted and observed probabilities in both sets. DCA showed that the nomogram had significant clinical utility. Conclusions The study successfully developed a nomogram predictive model for CSVD, incorporating nine clinical predictive factors. This model offers a valuable tool for early identification and risk assessment of CSVD, potentially enhancing clinical decision-making and patient outcomes.
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Affiliation(s)
- Ning Li
- Department of Neurology, Hebei Medical University, Shijiazhuang, China
- Department of Neurology, Affiliated Hospital of Hebei University, Baoding, China
| | - Ying-lei Li
- Department of Neurology, Hebei Medical University, Shijiazhuang, China
- Department of Emergency Medicine, Baoding First Central Hospital, Baoding, China
| | - Li-tao Li
- Department of Neurology, Hebei Medical University, Shijiazhuang, China
- Department of Neurology, Hebei General Hospital, Shijiazhuang, China
- Hebei Provincial Key Laboratory of Cerebral Networks and Cognitive Disorders, Hebei General Hospital, Shijiazhuang, China
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Wang Y, Liu Z. Research progress on the correlation between MRI and impairment caused by cerebral small vessel disease: A review. Medicine (Baltimore) 2023; 102:e35389. [PMID: 37800770 PMCID: PMC10553107 DOI: 10.1097/md.0000000000035389] [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] [Received: 04/13/2023] [Accepted: 09/05/2023] [Indexed: 10/07/2023] Open
Abstract
Cerebral small vessel disease (CSVD) is a chronic global brain disease mainly involving small blood vessels in the brain. The disease can be gradually aggravated with the increase of age, so it is the primary cause of brain dysfunction in the elderly. With the increasing aging of the world population and the high incidence of cerebrovascular risk factors, the incidence of CSVD is increasing day by day. CSVD is characterized by insidious onset, slow progression, diverse clinical manifestations, and difficult early diagnosis. CSVD can lead to cognitive impairment, gait impairment, affective impairment, and so on. however, it has not received enough attention from researchers in the past. In recent years, some studies have shown that CSVD patients have a high proportion of related impairment, which seriously affect patients daily life and social functions. Currently, no clear preventive measures or treatments exist to improve the condition. With the development of magnetic resonance imaging, CSVD has become more and more recognized and the detection rate has gradually improved. This paper reviews the research progress of magnetic resonance imaging and cognitive impairment, gait impairment, affective impairment, urination disorder, swallowing disorder, and other disorders to provide a useful reference for the early diagnosis and treatment of CSVD and expand new ideas.
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Affiliation(s)
- Yang Wang
- Department of Neurology, Xijing Hospital, Fourth Military Medical University, Xi’an, China
- Department of Neurology, 980th Hospital of PLA Joint Logistical Support Force (Bethune International Peace Hospital), Shijiazhuang, China
| | - Zhirong Liu
- Department of Neurology, Xijing Hospital, Fourth Military Medical University, Xi’an, China
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Prosser L, Macdougall A, Sudre CH, Manning EN, Malone IB, Walsh P, Goodkin O, Pemberton H, Barkhof F, Biessels GJ, Cash DM, Barnes J. Predicting Cognitive Decline in Older Adults Using Baseline Metrics of AD Pathologies, Cerebrovascular Disease, and Neurodegeneration. Neurology 2023; 100:e834-e845. [PMID: 36357185 PMCID: PMC9984210 DOI: 10.1212/wnl.0000000000201572] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2022] [Accepted: 09/28/2022] [Indexed: 11/12/2022] Open
Abstract
BACKGROUND AND OBJECTIVES Dementia is a growing socioeconomic challenge that requires early intervention. Identifying biomarkers that reliably predict clinical progression early in the disease process would better aid selection of individuals for future trial participation. Here, we compared the ability of baseline, single time-point biomarkers (CSF amyloid 1-42, CSF ptau-181, white matter hyperintensities (WMH), cerebral microbleeds, whole-brain volume, and hippocampal volume) to predict decline in cognitively normal individuals who later converted to mild cognitive impairment (MCI) (CNtoMCI) and those with MCI who later converted to an Alzheimer disease (AD) diagnosis (MCItoAD). METHODS Standardized baseline biomarker data from AD Neuroimaging Initiative 2 (ADNI2)/GO and longitudinal diagnostic data (including ADNI3) were used. Cox regression models assessed biomarkers in relation to time to change in clinical diagnosis using all follow-up time points available. Models were fit for biomarkers univariately and together in a multivariable model. Hazard ratios (HRs) were compared to evaluate biomarkers. Analyses were performed separately in CNtoMCI and MCItoAD groups. RESULTS For CNtoMCI (n = 189), there was strong evidence that higher WMH volume (individual model: HR 1.79, p = 0.002; fully adjusted model: HR 1.98, p = 0.003) and lower hippocampal volume (individual: HR 0.54, p = 0.001; fully adjusted: HR 0.40, p < 0.001) were associated with conversion to MCI individually and independently. For MCItoAD (n = 345), lower hippocampal (individual model: HR 0.45, p < 0.001; fully adjusted model: HR 0.55, p < 0.001) and whole-brain volume (individual: HR 0.31, p < 0.001; fully adjusted: HR 0.48, p = 0.02), increased CSF ptau (individual: HR 1.88, p < 0.001; fully adjusted: HR 1.61, p < 0.001), and lower CSF amyloid (individual: HR 0.37, p < 0.001; fully adjusted: HR 0.62, p = 0.008) were most strongly associated with conversion to AD individually and independently. DISCUSSION Lower hippocampal volume was a consistent predictor of clinical conversion to MCI and AD. CSF and brain volume biomarkers were predictive of conversion to AD from MCI, whereas WMH were predictive of conversion to MCI from cognitively normal. The predictive ability of WMH in the CNtoMCI group may be interpreted as some being on a different pathologic pathway, such as vascular cognitive impairment.
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Affiliation(s)
- Lloyd Prosser
- From the Department of Neurodegenerative Disease (L.P., A.M., C.H.S., E.N.M., I.B.M., P.W., H.P., D.M.C., J.B.), Dementia Research Centre, UCL Queen Square Institute of Neurology, London; Medical Statistics (A.M.), London School of Hygiene and Tropical Medicine; School of Biomedical Engineering and Imaging Sciences (C.H.S.), King's College London; Centre for Medical Image Computing (C.H.S., O.G., H.P., F.B.) and Department of Population Sciences and Experimental Medicine (C.H.S.), MRC Unit for Lifelong Health and Ageing at UCL, University College London, United Kingdom; Department of Radiology and Nuclear Medicine (F.B.), VU University Medical Center, Amsterdam Neuroscience; and Department of Neurology and Neurosurgery (G.J.B.), UMC Utrecht Brain Center, University Medical Center Utrecht, the Netherlands.
| | - Amy Macdougall
- From the Department of Neurodegenerative Disease (L.P., A.M., C.H.S., E.N.M., I.B.M., P.W., H.P., D.M.C., J.B.), Dementia Research Centre, UCL Queen Square Institute of Neurology, London; Medical Statistics (A.M.), London School of Hygiene and Tropical Medicine; School of Biomedical Engineering and Imaging Sciences (C.H.S.), King's College London; Centre for Medical Image Computing (C.H.S., O.G., H.P., F.B.) and Department of Population Sciences and Experimental Medicine (C.H.S.), MRC Unit for Lifelong Health and Ageing at UCL, University College London, United Kingdom; Department of Radiology and Nuclear Medicine (F.B.), VU University Medical Center, Amsterdam Neuroscience; and Department of Neurology and Neurosurgery (G.J.B.), UMC Utrecht Brain Center, University Medical Center Utrecht, the Netherlands
| | - Carole H Sudre
- From the Department of Neurodegenerative Disease (L.P., A.M., C.H.S., E.N.M., I.B.M., P.W., H.P., D.M.C., J.B.), Dementia Research Centre, UCL Queen Square Institute of Neurology, London; Medical Statistics (A.M.), London School of Hygiene and Tropical Medicine; School of Biomedical Engineering and Imaging Sciences (C.H.S.), King's College London; Centre for Medical Image Computing (C.H.S., O.G., H.P., F.B.) and Department of Population Sciences and Experimental Medicine (C.H.S.), MRC Unit for Lifelong Health and Ageing at UCL, University College London, United Kingdom; Department of Radiology and Nuclear Medicine (F.B.), VU University Medical Center, Amsterdam Neuroscience; and Department of Neurology and Neurosurgery (G.J.B.), UMC Utrecht Brain Center, University Medical Center Utrecht, the Netherlands
| | - Emily N Manning
- From the Department of Neurodegenerative Disease (L.P., A.M., C.H.S., E.N.M., I.B.M., P.W., H.P., D.M.C., J.B.), Dementia Research Centre, UCL Queen Square Institute of Neurology, London; Medical Statistics (A.M.), London School of Hygiene and Tropical Medicine; School of Biomedical Engineering and Imaging Sciences (C.H.S.), King's College London; Centre for Medical Image Computing (C.H.S., O.G., H.P., F.B.) and Department of Population Sciences and Experimental Medicine (C.H.S.), MRC Unit for Lifelong Health and Ageing at UCL, University College London, United Kingdom; Department of Radiology and Nuclear Medicine (F.B.), VU University Medical Center, Amsterdam Neuroscience; and Department of Neurology and Neurosurgery (G.J.B.), UMC Utrecht Brain Center, University Medical Center Utrecht, the Netherlands
| | - Ian B Malone
- From the Department of Neurodegenerative Disease (L.P., A.M., C.H.S., E.N.M., I.B.M., P.W., H.P., D.M.C., J.B.), Dementia Research Centre, UCL Queen Square Institute of Neurology, London; Medical Statistics (A.M.), London School of Hygiene and Tropical Medicine; School of Biomedical Engineering and Imaging Sciences (C.H.S.), King's College London; Centre for Medical Image Computing (C.H.S., O.G., H.P., F.B.) and Department of Population Sciences and Experimental Medicine (C.H.S.), MRC Unit for Lifelong Health and Ageing at UCL, University College London, United Kingdom; Department of Radiology and Nuclear Medicine (F.B.), VU University Medical Center, Amsterdam Neuroscience; and Department of Neurology and Neurosurgery (G.J.B.), UMC Utrecht Brain Center, University Medical Center Utrecht, the Netherlands
| | - Phoebe Walsh
- From the Department of Neurodegenerative Disease (L.P., A.M., C.H.S., E.N.M., I.B.M., P.W., H.P., D.M.C., J.B.), Dementia Research Centre, UCL Queen Square Institute of Neurology, London; Medical Statistics (A.M.), London School of Hygiene and Tropical Medicine; School of Biomedical Engineering and Imaging Sciences (C.H.S.), King's College London; Centre for Medical Image Computing (C.H.S., O.G., H.P., F.B.) and Department of Population Sciences and Experimental Medicine (C.H.S.), MRC Unit for Lifelong Health and Ageing at UCL, University College London, United Kingdom; Department of Radiology and Nuclear Medicine (F.B.), VU University Medical Center, Amsterdam Neuroscience; and Department of Neurology and Neurosurgery (G.J.B.), UMC Utrecht Brain Center, University Medical Center Utrecht, the Netherlands
| | - Olivia Goodkin
- From the Department of Neurodegenerative Disease (L.P., A.M., C.H.S., E.N.M., I.B.M., P.W., H.P., D.M.C., J.B.), Dementia Research Centre, UCL Queen Square Institute of Neurology, London; Medical Statistics (A.M.), London School of Hygiene and Tropical Medicine; School of Biomedical Engineering and Imaging Sciences (C.H.S.), King's College London; Centre for Medical Image Computing (C.H.S., O.G., H.P., F.B.) and Department of Population Sciences and Experimental Medicine (C.H.S.), MRC Unit for Lifelong Health and Ageing at UCL, University College London, United Kingdom; Department of Radiology and Nuclear Medicine (F.B.), VU University Medical Center, Amsterdam Neuroscience; and Department of Neurology and Neurosurgery (G.J.B.), UMC Utrecht Brain Center, University Medical Center Utrecht, the Netherlands
| | - Hugh Pemberton
- From the Department of Neurodegenerative Disease (L.P., A.M., C.H.S., E.N.M., I.B.M., P.W., H.P., D.M.C., J.B.), Dementia Research Centre, UCL Queen Square Institute of Neurology, London; Medical Statistics (A.M.), London School of Hygiene and Tropical Medicine; School of Biomedical Engineering and Imaging Sciences (C.H.S.), King's College London; Centre for Medical Image Computing (C.H.S., O.G., H.P., F.B.) and Department of Population Sciences and Experimental Medicine (C.H.S.), MRC Unit for Lifelong Health and Ageing at UCL, University College London, United Kingdom; Department of Radiology and Nuclear Medicine (F.B.), VU University Medical Center, Amsterdam Neuroscience; and Department of Neurology and Neurosurgery (G.J.B.), UMC Utrecht Brain Center, University Medical Center Utrecht, the Netherlands
| | - Frederik Barkhof
- From the Department of Neurodegenerative Disease (L.P., A.M., C.H.S., E.N.M., I.B.M., P.W., H.P., D.M.C., J.B.), Dementia Research Centre, UCL Queen Square Institute of Neurology, London; Medical Statistics (A.M.), London School of Hygiene and Tropical Medicine; School of Biomedical Engineering and Imaging Sciences (C.H.S.), King's College London; Centre for Medical Image Computing (C.H.S., O.G., H.P., F.B.) and Department of Population Sciences and Experimental Medicine (C.H.S.), MRC Unit for Lifelong Health and Ageing at UCL, University College London, United Kingdom; Department of Radiology and Nuclear Medicine (F.B.), VU University Medical Center, Amsterdam Neuroscience; and Department of Neurology and Neurosurgery (G.J.B.), UMC Utrecht Brain Center, University Medical Center Utrecht, the Netherlands
| | - Geert Jan Biessels
- From the Department of Neurodegenerative Disease (L.P., A.M., C.H.S., E.N.M., I.B.M., P.W., H.P., D.M.C., J.B.), Dementia Research Centre, UCL Queen Square Institute of Neurology, London; Medical Statistics (A.M.), London School of Hygiene and Tropical Medicine; School of Biomedical Engineering and Imaging Sciences (C.H.S.), King's College London; Centre for Medical Image Computing (C.H.S., O.G., H.P., F.B.) and Department of Population Sciences and Experimental Medicine (C.H.S.), MRC Unit for Lifelong Health and Ageing at UCL, University College London, United Kingdom; Department of Radiology and Nuclear Medicine (F.B.), VU University Medical Center, Amsterdam Neuroscience; and Department of Neurology and Neurosurgery (G.J.B.), UMC Utrecht Brain Center, University Medical Center Utrecht, the Netherlands
| | - David M Cash
- From the Department of Neurodegenerative Disease (L.P., A.M., C.H.S., E.N.M., I.B.M., P.W., H.P., D.M.C., J.B.), Dementia Research Centre, UCL Queen Square Institute of Neurology, London; Medical Statistics (A.M.), London School of Hygiene and Tropical Medicine; School of Biomedical Engineering and Imaging Sciences (C.H.S.), King's College London; Centre for Medical Image Computing (C.H.S., O.G., H.P., F.B.) and Department of Population Sciences and Experimental Medicine (C.H.S.), MRC Unit for Lifelong Health and Ageing at UCL, University College London, United Kingdom; Department of Radiology and Nuclear Medicine (F.B.), VU University Medical Center, Amsterdam Neuroscience; and Department of Neurology and Neurosurgery (G.J.B.), UMC Utrecht Brain Center, University Medical Center Utrecht, the Netherlands
| | - Josephine Barnes
- From the Department of Neurodegenerative Disease (L.P., A.M., C.H.S., E.N.M., I.B.M., P.W., H.P., D.M.C., J.B.), Dementia Research Centre, UCL Queen Square Institute of Neurology, London; Medical Statistics (A.M.), London School of Hygiene and Tropical Medicine; School of Biomedical Engineering and Imaging Sciences (C.H.S.), King's College London; Centre for Medical Image Computing (C.H.S., O.G., H.P., F.B.) and Department of Population Sciences and Experimental Medicine (C.H.S.), MRC Unit for Lifelong Health and Ageing at UCL, University College London, United Kingdom; Department of Radiology and Nuclear Medicine (F.B.), VU University Medical Center, Amsterdam Neuroscience; and Department of Neurology and Neurosurgery (G.J.B.), UMC Utrecht Brain Center, University Medical Center Utrecht, the Netherlands
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Zhao J, Wang X, Li Q, Lu C, Li S. The relevance of serum macrophage migratory inhibitory factor and cognitive dysfunction in patients with cerebral small vascular disease. Front Aging Neurosci 2023; 15:1083818. [PMID: 36824264 PMCID: PMC9941340 DOI: 10.3389/fnagi.2023.1083818] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2022] [Accepted: 01/18/2023] [Indexed: 02/10/2023] Open
Abstract
Cerebral small vascular disease (CSVD) is a common type of cerebrovascular disease, and an important cause of vascular cognitive impairment (VCI) and stroke. The disease burden is expected to increase further as a result of population aging, an ongoing high prevalence of risk factors (e.g., hypertension), and inadequate management. Due to the poor understanding of pathophysiology in CSVD, there is no effective preventive or therapeutic approach for CSVD. Macrophage migration inhibitory factor (MIF) is a multifunctional cytokine that is related to the occurrence and development of vascular dysfunction diseases. Therefore, MIF may contribute to the pathogenesis of CSVD and VCI. Here, reviewed MIF participation in chronic cerebral ischemia-hypoperfusion and neurodegeneration pathology, including new evidence for CSVD, and its potential role in protection against VCI.
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Affiliation(s)
- Jianhua Zhao
- Henan Joint International Research Laboratory of Neurorestoratology for Senile Dementia, Henan Key Laboratory of Neurorestoratology, Department of Neurology, First Affiliated Hospital of Xinxiang Medical University, Xinxiang, Henan, China,*Correspondence: Jianhua Zhao,
| | - Xiaoting Wang
- Henan Joint International Research Laboratory of Neurorestoratology for Senile Dementia, Henan Key Laboratory of Neurorestoratology, Department of Neurology, First Affiliated Hospital of Xinxiang Medical University, Xinxiang, Henan, China
| | - Qiong Li
- Henan Joint International Research Laboratory of Neurorestoratology for Senile Dementia, Henan Key Laboratory of Neurorestoratology, Department of Neurology, First Affiliated Hospital of Xinxiang Medical University, Xinxiang, Henan, China
| | - Chengbiao Lu
- Sino-UK Joint Laboratory of Brain Function and Injury of Henan Province, Department of Physiology and Neurobiology, Xinxiang Medical University, Xinxiang, China
| | - Shaomin Li
- Ann Romney Center for Neurologic Diseases, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, United States
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Hussein AS, Shawqi M, Bahbah EI, Ragab B, Sunoqrot M, Gadallah A, Ghaith HS, Negida A. Do cerebral microbleeds increase the risk of dementia? A systematic review and meta-analysis. IBRO Neurosci Rep 2022; 14:86-94. [PMID: 36632242 PMCID: PMC9827375 DOI: 10.1016/j.ibneur.2022.12.009] [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: 05/14/2022] [Accepted: 12/26/2022] [Indexed: 12/29/2022] Open
Abstract
Background Dementia is a neurological disorder that commonly affects the elderly. Cerebral microbleeds (CMBs) are small, tiny lesions of the cerebral blood vessels and have been suggested as a possible risk factor for dementia. However, data about the association between CMBs and dementia risk are inconsistent and inconclusive. Therefore, we conducted this systematic review and meta-analysis to investigate the association between CMBs and dementia and highlight the possible explanations. Methods We followed the standard PRISMA statement and the Cochrane Handbook guidelines to conduct this study. First, we searched medical electronic databases for relevant articles. Then, we screened the retrieved articles for eligibility, extracted the relevant data, and appraised the methodological quality using the Newcastle-Ottawa Scale. Finally, the extracted data were pooled as risk ratios (RR) and hazard ratios (HR) in the random-effects meta-analysis model using the Review Manager software. Results We included nine studies with 14,221 participants and follow-up periods > 18 months. Overall, CMBs significantly increased the risk of developing dementia (RR 1.84, 95% CI [1.27-2.65]). This association was significant in the subgroups of studies on high-risk populations (RR 2.00, 95% CI [1.41-2.83], n = 1657 participants) and those in the general population (RR 2.30, 95% CI [1.25-4.26], n = 12,087 participants) but not in the memory clinic patients. Further, CMBs increased the risk of progressing to incident dementia over time (HR 2, 95% CI [1.54-2.61]). Conclusion Individuals with CMBs have twice the risk of developing dementia or progressing to MCI than those without CMBs. The detection of CMBs will help identify the population at higher risk of developing dementia. Physicians should educate individuals with CMBs and their families on the possibility of progressing to dementia or MCI. Regular cognitive assessments, cognitive training, lifestyle modifications, and controlling other dementia risk factors are recommended for individuals with CMBs to decrease the risk of cognitive decline and dementia development.
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Affiliation(s)
- Ahmed Salah Hussein
- Medical Research Group of Egypt (MRGE), Cairo, Egypt,Faculty of Medicine, Al-Azhar University, Cairo, Egypt
| | - Muhammad Shawqi
- Medical Research Group of Egypt (MRGE), Cairo, Egypt,Faculty of Medicine, Assiut University, Assiut, Egypt
| | - Eshak I. Bahbah
- Medical Research Group of Egypt (MRGE), Cairo, Egypt,Faculty of Medicine, Al-Azhar University, Damietta, Egypt
| | - Basma Ragab
- Medical Research Group of Egypt (MRGE), Cairo, Egypt,Faculty of Physical Therapy, Cairo University, Cairo, Egypt
| | - Mohammad Sunoqrot
- Medical Research Group of Egypt (MRGE), Cairo, Egypt,Faculty of Medicine, Cairo University, Cairo, Egypt
| | - Ahmed Gadallah
- Medical Research Group of Egypt (MRGE), Cairo, Egypt,Ain Shams University Hospitals, Cairo, Egypt
| | - Hazem S. Ghaith
- Medical Research Group of Egypt (MRGE), Cairo, Egypt,Faculty of Medicine, Al-Azhar University, Cairo, Egypt
| | - Ahmed Negida
- Medical Research Group of Egypt (MRGE), Cairo, Egypt,Faculty of Medicine, Zagazig University, Egypt,School of Pharmacy and Biomedical Sciences, University of Portsmouth, United Kingdom,Department of Global Health and Social Medicine, Harvard Medical School, MA, USA,Correspondence to: Harvard Medical School, 641 Huntington Avenue, Boston, MA 02115, USA.
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Guo W, Shi J. White matter hyperintensities volume and cognition: A meta-analysis. Front Aging Neurosci 2022; 14:949763. [PMID: 36118701 PMCID: PMC9476945 DOI: 10.3389/fnagi.2022.949763] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2022] [Accepted: 08/08/2022] [Indexed: 11/13/2022] Open
Abstract
Background Cerebral small vessel disease (CSVD) is prevalent in the elderly and leads to an increased risk of cognitive impairment and dementia. The volume of white matter hyperintensities (WMHs) increases with age, which affects cognition. Objective To explore the relationship between WMH volume and cognitive decline in patients with CSVD. Methods We performed a systematic search of PubMed, Embase, and the Web of Science databases from their respective creation dates to the 5 May 2022 to identify all the clinical studies on either mild cognitive impairment (MCI) or dementia in regards to WMH volume in CSVD. Results White matter hyperintensities was associated with the risk of both the MCI and dementia, with a 35% increased risk [relative risk (RR) = 1.35; (95% CI: 1.01–1.81)] of progression from cognitively unimpaired (CU) to MCI (six studies, n = 2,278) and a 49% increased risk [RR = 1.49; (95% CI: 1.21–1.84)] of progression to dementia (six studies, n = 6,330). In a subgroup analysis, a follow-up period of over 5 years increased the risk of MCI by 40% [RR = 1.40; (95% CI: 1.07–1.82)] and dementia by 48% [RR = 1.48; (95% CI: 1.15–1.92)]. Conclusion White matter hyperintensities was found to be substantially correlated with the risk of cognitive impairment. Furthermore, cognitive decline was found to be a chronic process, such that WMH predicted the rate of cognitive decline in CSVD beyond 5 years. The cognitive decline observed in patients with WMH may, therefore, be minimized by early intervention.
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Chung CP, Lee WJ, Chou KH, Lee PL, Peng LN, Wang PN, Lin CP, Chen LK. Frailty and dementia risks in asymptomatic cerebral small vessel disease: A longitudinal cohort study. Arch Gerontol Geriatr 2022; 102:104754. [PMID: 35728329 DOI: 10.1016/j.archger.2022.104754] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2022] [Revised: 06/12/2022] [Accepted: 06/13/2022] [Indexed: 11/30/2022]
Abstract
OBJECTIVES Frailty has been shown to predict adverse outcomes in several diseases. We aimed to evaluate the associations between frailty profiles, both severity and subtype, and dementia risk in a community-based population with asymptomatic (without stroke and dementia) cerebral small vessel disease (CSVD). METHODS Individuals with asymptomatic CSVD were recruited from the community-based I-Lan Longitudinal Aging Study between 2011 and 2014 (baseline) and were followed up between 2018 and 2019. All participants underwent CSVD assessment by 3T brain MRI, as well as physical and cognitive assessments at baseline. Univariate and multivariate logistic regression analyses were performed to evaluate the associations between each factor and dementia conversion at follow-up. RESULTS Among 261 participants with asymptomatic CSVD (64.8 [50.0-89.1, 8.4] years; 136 [52.1%] men), 13 (5.0%) developed dementia during a mean follow-up of 5.7 (0.7) years. Dementia converters were less likely to be robust (30.8% vs. 61.5%) and more likely to be pre-frail/frail (69.2% vs. 38.5%) than non-converters (p = 0.040). Meanwhile, there was significantly more frequent mobility frailty (53.8% vs. 19.8%, p = 0.009), but a similar prevalence of non-mobility frailty in dementia converters compared with non-converters. Univariate analyses showed that neither frailty severity nor CSVD burden was associated with a higher risk of dementia; it was the frailty subtype, the mobility frailty, which was significantly associated with dementia conversion in participants with asymptomatic CSVD, with an odds-ratio of 4.8 (95% CI = 1.5-14.8, p = 0.007). The significance remained after adjusting for age, sex, education and baseline cognitive function, respectively. CONCLUSION Mobility frailty was associated with a higher risk of incident dementia in individuals with subclinical CSVD. Mobility frailty might be involved in the pathology of cognitive decline in CSVD and potentially serve as a marker to identify people at risk of cognitive impairment at an early stage of CSVD.
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Affiliation(s)
- Chih-Ping Chung
- Department of Neurology, Neurological Institute, Taipei Veterans General Hospital, No. 201, Section 2, Shipai Road, Beitou District, Taipei City 112, Taiwan; School of Medicine, National Yang Ming Chiao Tung University College of Medicine, Taipei, Taiwan.
| | - Wei-Ju Lee
- Aging and Health Research Center, National Yang Ming Chiao Tung University College of Medicine, Taipei, Taiwan; Department of Family Medicine, Taipei Veterans General Hospital Yuanshan Branch, Yi-Lan, Taiwan
| | - Kun-Hsien Chou
- Institute of Neuroscience, National Yang Ming Chiao Tung University College of Medicine, Taipei, Taiwan; Brain Research Center, National Yang Ming Chiao Tung University College of Medicine, Taipei, Taiwan
| | - Pei-Lin Lee
- Institute of Neuroscience, National Yang Ming Chiao Tung University College of Medicine, Taipei, Taiwan; Brain Research Center, National Yang Ming Chiao Tung University College of Medicine, Taipei, Taiwan
| | - Li-Ning Peng
- Aging and Health Research Center, National Yang Ming Chiao Tung University College of Medicine, Taipei, Taiwan; Center for Geriatric and Gerontology, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Pei-Ning Wang
- Department of Neurology, Neurological Institute, Taipei Veterans General Hospital, No. 201, Section 2, Shipai Road, Beitou District, Taipei City 112, Taiwan; Aging and Health Research Center, National Yang Ming Chiao Tung University College of Medicine, Taipei, Taiwan; Brain Research Center, National Yang Ming Chiao Tung University College of Medicine, Taipei, Taiwan; School of Medicine, National Yang Ming Chiao Tung University College of Medicine, Taipei, Taiwan
| | - Ching-Po Lin
- Institute of Neuroscience, National Yang Ming Chiao Tung University College of Medicine, Taipei, Taiwan; Brain Research Center, National Yang Ming Chiao Tung University College of Medicine, Taipei, Taiwan
| | - Liang-Kung Chen
- Aging and Health Research Center, National Yang Ming Chiao Tung University College of Medicine, Taipei, Taiwan; Taipei Municipal Gan-Dau Hospital (managed by Taipei Veterans General Hospital), Taipei, Taiwan
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8
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Kelly DM, Rothwell PM. Disentangling the Relationship Between Chronic Kidney Disease and Cognitive Disorders. Front Neurol 2022; 13:830064. [PMID: 35280286 PMCID: PMC8914950 DOI: 10.3389/fneur.2022.830064] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2021] [Accepted: 02/03/2022] [Indexed: 12/12/2022] Open
Abstract
Chronic kidney disease (CKD) is a rapidly rising global health burden that affects nearly 40% of older adults. Epidemiologic data suggest that individuals at all stages of chronic kidney disease (CKD) have a higher risk of developing cognitive disorders and dementia, and thus represent a vulnerable population. It is currently unknown to what extent this risk may be attributable to a clustering of traditional risk factors such as hypertension and diabetes mellitus leading to a high prevalence of both symptomatic and subclinical ischaemic cerebrovascular lesions, or whether other potential mechanisms, including direct neuronal injury by uraemic toxins or dialysis-specific factors could also be involved. These knowledge gaps may lead to suboptimal prevention and treatment strategies being implemented in this group. In this review, we explore the mechanisms of susceptibility and risk in the relationship between CKD and cognitive disorders.
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Affiliation(s)
- Dearbhla M. Kelly
- J. Philip Kistler Stroke Research Center, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
| | - Peter M. Rothwell
- Wolfson Center for Prevention of Stroke and Dementia, Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, United Kingdom
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9
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Montandon ML, Herrmann FR, Garibotto V, Rodriguez C, Haller S, Giannakopoulos P. Microbleeds and Medial Temporal Atrophy Determine Cognitive Trajectories in Normal Aging: A Longitudinal PET-MRI Study. J Alzheimers Dis 2021; 77:1431-1442. [PMID: 32925053 DOI: 10.3233/jad-200559] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/16/2023]
Abstract
BACKGROUND The cognitive trajectories in normal aging may be affected by medial temporal atrophy (MTA) and amyloid burden, as well as vascular pathologies such as cortical microbleeds (CMB) and white matter hyperintensities (WMH). OBJECTIVE We addressed here the role of imaging markers in their prediction in a real-world situation. METHODS We performed a 4.5-year longitudinal study in 90 older community-dwellers coupling two neuropsychological assessments, MTA estimated with the Schelten's scale, number of CMB, and WMH evaluated with the Fazekas score at inclusion and follow-up, visual rating of amyloid PET and glucose hypometabolism at follow-up, and APOE genotyping. Regression models were built to explore the association between the continuous cognitive score (CCS) and imaging parameters. RESULTS The number of strictly lobar CMB at baseline (4 or more) was related to a 5.5-fold increase of the risk of cognitive decrement. This association persisted in multivariable models explaining 10.6% of the CCS decrease variance. MTA, and Fazekas score at baseline and amyloid positivity or abnormal FDG PET, were not related to the cognitive outcome. The increase of right MTA at follow-up was the only correlate of CCS decrease both in univariate and multivariable models explaining 9.2% of its variance. CONCLUSION The present data show that the accumulation of more than four CMB is associated with significant cognitive decrement over time in highly educated elderly persons. They also reveal that the progressive deterioration of cognitive performance within the age-adjusted norms is also related to the increase of visually assessed MTA.
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Affiliation(s)
- Marie-Louise Montandon
- Department of Rehabilitation and Geriatrics, Geneva University Hospitals and University of Geneva, Switzerland.,Department of Psychiatry, University of Geneva, Switzerland
| | - François R Herrmann
- Department of Rehabilitation and Geriatrics, Geneva University Hospitals and University of Geneva, Switzerland
| | - Valentina Garibotto
- Division of Nuclear Medicine and Molecular Imaging, Diagnostic Department, Geneva University Hospitals and University of Geneva, Switzerland
| | - Cristelle Rodriguez
- Department of Psychiatry, University of Geneva, Switzerland.,Medical Direction, University of Geneva Hospitals, Geneva, Switzerland
| | - Sven Haller
- CIRD - Centre d'Imagerie Rive Droite in Geneva, Switzerland.,Department of Surgical Sciences, Radiology, Uppsala University, Uppsala, Sweden.,Department of Neuroradiology, Faculty of Medicine of the University of Geneva, Geneva, Switzerland
| | - Panteleimon Giannakopoulos
- Department of Psychiatry, University of Geneva, Switzerland.,Medical Direction, University of Geneva Hospitals, Geneva, Switzerland
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10
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Wang M, Hu HY, Wang ZT, Ou YN, Qu Y, Ma YH, Dong Q, Tan L, Yu JT. Association of cerebral microbleeds with risks of cognitive impairment and dementia: A systematic review and meta-analysis of prospective studies. BRAIN DISORDERS 2021. [DOI: 10.1016/j.dscb.2021.100010] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
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11
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Hamilton OKL, Backhouse EV, Janssen E, Jochems ACC, Maher C, Ritakari TE, Stevenson AJ, Xia L, Deary IJ, Wardlaw JM. Cognitive impairment in sporadic cerebral small vessel disease: A systematic review and meta-analysis. Alzheimers Dement 2021; 17:665-685. [PMID: 33185327 PMCID: PMC8593445 DOI: 10.1002/alz.12221] [Citation(s) in RCA: 82] [Impact Index Per Article: 27.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2020] [Revised: 02/08/2020] [Accepted: 05/10/2020] [Indexed: 01/09/2023]
Abstract
This paper is a proposal for an update on the characterization of cognitive impairments associated with sporadic cerebral small vessel disease (SVD). We pose a series of questions about the nature of SVD-related cognitive impairments and provide answers based on a comprehensive review and meta-analysis of published data from 69 studies. Although SVD is thought primarily to affect executive function and processing speed, we hypothesize that SVD affects all major domains of cognitive ability. We also identify low levels of education as a potentially modifiable risk factor for SVD-related cognitive impairment. Therefore, we propose the use of comprehensive cognitive assessments and the measurement of educational level both in clinics and research settings, and suggest several recommendations for future research.
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Affiliation(s)
- Olivia KL Hamilton
- Centre for Clinical Brain Sciences, University of Edinburgh, Chancellor’s Building, 49 Little France Crescent, Edinburgh, UK, EH16 4SB
- Dementia Research Institute, University of Edinburgh, Chancellor’s Building, 49 Little France Crescent, Edinburgh, UK, EH16 4SB
- Lothian Birth Cohorts, University of Edinburgh, 7 George Square, Edinburgh, UK, EH8 9JZ
| | - Ellen V Backhouse
- Centre for Clinical Brain Sciences, University of Edinburgh, Chancellor’s Building, 49 Little France Crescent, Edinburgh, UK, EH16 4SB
- Dementia Research Institute, University of Edinburgh, Chancellor’s Building, 49 Little France Crescent, Edinburgh, UK, EH16 4SB
| | - Esther Janssen
- Centre for Clinical Brain Sciences, University of Edinburgh, Chancellor’s Building, 49 Little France Crescent, Edinburgh, UK, EH16 4SB
- Dementia Research Institute, University of Edinburgh, Chancellor’s Building, 49 Little France Crescent, Edinburgh, UK, EH16 4SB
| | - Angela CC Jochems
- Centre for Clinical Brain Sciences, University of Edinburgh, Chancellor’s Building, 49 Little France Crescent, Edinburgh, UK, EH16 4SB
- Dementia Research Institute, University of Edinburgh, Chancellor’s Building, 49 Little France Crescent, Edinburgh, UK, EH16 4SB
| | - Caragh Maher
- Centre for Clinical Brain Sciences, University of Edinburgh, Chancellor’s Building, 49 Little France Crescent, Edinburgh, UK, EH16 4SB
- Dementia Research Institute, University of Edinburgh, Chancellor’s Building, 49 Little France Crescent, Edinburgh, UK, EH16 4SB
| | - Tuula E Ritakari
- Centre for Clinical Brain Sciences, University of Edinburgh, Chancellor’s Building, 49 Little France Crescent, Edinburgh, UK, EH16 4SB
- Dementia Research Institute, University of Edinburgh, Chancellor’s Building, 49 Little France Crescent, Edinburgh, UK, EH16 4SB
| | - Anna J Stevenson
- Dementia Research Institute, University of Edinburgh, Chancellor’s Building, 49 Little France Crescent, Edinburgh, UK, EH16 4SB
- Centre for Genomic and Experimental Medicine, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital Campus, Crewe Road, Edinburgh, UK, EH4 2XU
- Centre for Discovery Brain Sciences, University of Edinburgh, Hugh Robson Building, 15 George Square, Edinburgh, UK, EH8 9XD
| | - Lihua Xia
- Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh, UK, EH8 9JZ
| | - Ian J Deary
- Lothian Birth Cohorts, University of Edinburgh, 7 George Square, Edinburgh, UK, EH8 9JZ
- Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh, UK, EH8 9JZ
| | - Joanna M Wardlaw
- Centre for Clinical Brain Sciences, University of Edinburgh, Chancellor’s Building, 49 Little France Crescent, Edinburgh, UK, EH16 4SB
- Dementia Research Institute, University of Edinburgh, Chancellor’s Building, 49 Little France Crescent, Edinburgh, UK, EH16 4SB
- Lothian Birth Cohorts, University of Edinburgh, 7 George Square, Edinburgh, UK, EH8 9JZ
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12
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Verdelho A, Wardlaw J, Pavlovic A, Pantoni L, Godefroy O, Duering M, Charidimou A, Chabriat H, Biessels GJ. Cognitive impairment in patients with cerebrovascular disease: A white paper from the links between stroke ESO Dementia Committee. Eur Stroke J 2021; 6:5-17. [PMID: 33817330 PMCID: PMC7995319 DOI: 10.1177/23969873211000258] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2021] [Accepted: 02/04/2021] [Indexed: 12/21/2022] Open
Abstract
PURPOSE Many daily-life clinical decisions in patients with cerebrovascular disease and cognitive impairment are complex. Evidence-based information sustaining these decisions is frequently lacking. The aim of this paper is to propose a practical clinical approach to cognitive impairments in patients with known cerebrovascular disease. METHODS The document was produced by the Dementia Committee of the European Stroke Organisation (ESO), based on evidence from the literature where available and on the clinical experience of the Committee members. This paper was endorsed by the ESO. FINDINGS Many patients with stroke or other cerebrovascular disease have cognitive impairment, but this is often not recognized. With improvement in acute stroke care, and with the ageing of populations, it is expected that more stroke survivors and more patients with cerebrovascular disease will need adequate management of cognitive impairment of vascular etiology. This document was conceived for the use of strokologists and for those clinicians involved in cerebrovascular disease, with specific and practical hints concerning diagnostic tools, cognitive impairment management and decision on some therapeutic options.Discussion and conclusions: It is essential to consider a possible cognitive deterioration in every patient who experiences a stroke. Neuropsychological evaluation should be adapted to the clinical status. Brain imaging is the most informative biomarker concerning prognosis. Treatment should always include adequate secondary prevention.
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Affiliation(s)
- Ana Verdelho
- Department of Neurosciences and Mental Health, CHLN-Hospital de Santa Maria, Instituto de Medicina Molecular – IMM e Instituto de Saúde Ambiental –ISAMB, Faculdade de Medicina, University of Lisbon, Lisbon, Portugal
| | - Joanna Wardlaw
- Centre for Clinical Brain Sciences, UK Dementia Research Institute, University of Edinburgh, Edinburgh, UK
| | - Aleksandra Pavlovic
- Faculty for Special Education and Rehabilitation, University of Belgrade, Belgrade, Serbia
| | - Leonardo Pantoni
- Stroke and Dementia Lab, "Luigi Sacco" Department of Biomedical and Clinical Sciences, University of Milan, Milan, Italy
| | - Olivier Godefroy
- Department of Neurology, Amiens University Hospital, Laboratory of Functional Neurosciences1,6 (UR UPJV 4559), Jules Verne Picardy University, Amiens, France
| | - Marco Duering
- Institute for Stroke and Dementia Research, University Hospital, LMU Munich, Germany
- Department of Biomedical Engineering, University of Basel, Basel, Switzerland
| | - Andreas Charidimou
- Hemorrhagic Stroke Research Program, J. Philip Kistler Stroke Research Center, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Department of Neurology, Boston Medical Center, Boston University School of Medicine, Boston, MA, USA
| | - Hugues Chabriat
- Department of Neurology, FHU NeuroVasc, Hôpital Lariboisiere, University of Paris, Paris, France
| | - Geert Jan Biessels
- Department of Neurology, UMC Utrecht Brain Center, University Medical Center Utrecht, the Netherlands
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13
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Nassir CMNCM, Ghazali MM, Hashim S, Idris NS, Yuen LS, Hui WJ, Norman HH, Gau CH, Jayabalan N, Na Y, Feng L, Ong LK, Abdul Hamid H, Ahamed HN, Mustapha M. Diets and Cellular-Derived Microparticles: Weighing a Plausible Link With Cerebral Small Vessel Disease. Front Cardiovasc Med 2021; 8:632131. [PMID: 33718454 PMCID: PMC7943466 DOI: 10.3389/fcvm.2021.632131] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2020] [Accepted: 01/19/2021] [Indexed: 12/24/2022] Open
Abstract
Cerebral small vessel disease (CSVD) represents a spectrum of pathological processes of various etiologies affecting the brain microcirculation that can trigger neuroinflammation and the subsequent neurodegenerative cascade. Prevalent with aging, CSVD is a recognized risk factor for stroke, vascular dementia, Alzheimer disease, and Parkinson disease. Despite being the most common neurodegenerative condition with cerebrocardiovascular axis, understanding about it remains poor. Interestingly, modifiable risk factors such as unhealthy diet including high intake of processed food, high-fat foods, and animal by-products are known to influence the non-neural peripheral events, such as in the gastrointestinal tract and cardiovascular stress through cellular inflammation and oxidation. One key outcome from such events, among others, includes the cellular activations that lead to elevated levels of endogenous cellular-derived circulating microparticles (MPs). MPs can be produced from various cellular origins including leukocytes, platelets, endothelial cells, microbiota, and microglia. MPs could act as microthrombogenic procoagulant that served as a plausible culprit for the vulnerable end-artery microcirculation in the brain as the end-organ leading to CSVD manifestations. However, little attention has been paid on the potential role of MPs in the onset and progression of CSVD spectrum. Corroboratively, the formation of MPs is known to be influenced by diet-induced cellular stress. Thus, this review aims to appraise the body of evidence on the dietary-related impacts on circulating MPs from non-neural peripheral origins that could serve as a plausible microthrombosis in CSVD manifestation as a precursor of neurodegeneration. Here, we elaborate on the pathomechanical features of MPs in health and disease states; relevance of dietary patterns on MP release; preclinical studies pertaining to diet-based MPs contribution to disease; MP level as putative surrogates for early disease biomarkers; and lastly, the potential of MPs manipulation with diet-based approach as a novel preventive measure for CSVD in an aging society worldwide.
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Affiliation(s)
| | - Mazira Mohamad Ghazali
- Department of Neurosciences, School of Medical Sciences, Universiti Sains Malaysia, Kubang Kerian, Malaysia
| | - Sabarisah Hashim
- Department of Neurosciences, School of Medical Sciences, Universiti Sains Malaysia, Kubang Kerian, Malaysia
| | - Nur Suhaila Idris
- Department of Family Medicine, School of Medical Sciences, Universiti Sains Malaysia, Kubang Kerian, Malaysia
| | - Lee Si Yuen
- Department of Internal Medicine, School of Medical Sciences, Universiti Sains Malaysia, Kubang Kerian, Malaysia
| | - Wong Jia Hui
- Neurobiology of Aging and Disease Laboratory, Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
| | - Haziq Hazman Norman
- Anatomy Unit, International Medical School (IMS), Management and Science University (MSU), Shah Alam, Malaysia
| | - Chuang Huei Gau
- Department of Psychology and Counselling, Faculty of Arts and Social Science, Universiti Tunku Abdul Rahman (UTAR), Kampar, Malaysia
| | - Nanthini Jayabalan
- Translational Neuroscience Lab, University of Queensland (UQ), Centre for Clinical Research, The University of Queensland, Herston, QLD, Australia
| | - Yuri Na
- Center for Functional Connectomics, Brain Science Institute, Korea Institute of Science and Technology (KIST), Seoul, South Korea
| | - Linqing Feng
- Center for Functional Connectomics, Brain Science Institute, Korea Institute of Science and Technology (KIST), Seoul, South Korea
| | - Lin Kooi Ong
- School of Pharmacy, Monash University Malaysia, Bandar Sunway, Malaysia
- School of Biomedical Sciences and Pharmacy, Priority Research Centre for Stroke and Brain Injury, University of Newcastle, Callaghan, NSW, Australia
- Hunter Medical Research Institute, New Lambton Heights, NSW, Australia
- Centre of Research Excellence Stroke Rehabilitation and Brain Recovery, National Health and Medical Research Council (NHMRC), Heidelberg, VIC, Australia
| | - Hafizah Abdul Hamid
- Department of Human Anatomy, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, Serdang, Malaysia
| | - Haja Nazeer Ahamed
- Crescent School of Pharmacy, B.S. Abdur Rahman Crescent Institute of Science and Technology, Chennai, India
| | - Muzaimi Mustapha
- Department of Neurosciences, School of Medical Sciences, Universiti Sains Malaysia, Kubang Kerian, Malaysia
- Hospital Universiti Sains Malaysia, Jalan Raja Perempuan Zainab II, Kubang Kerian, Malaysia
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14
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Associations between left ventricular function, vascular function and measures of cerebral small vessel disease: a cross-sectional magnetic resonance imaging study of the UK Biobank. Eur Radiol 2021; 31:5068-5076. [PMID: 33409793 DOI: 10.1007/s00330-020-07567-1] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2020] [Revised: 09/22/2020] [Accepted: 11/26/2020] [Indexed: 10/22/2022]
Abstract
OBJECTIVES Impaired cardiovascular function has been associated with cognitive deterioration; however, to what extent cardiovascular dysfunction plays a role in structural cerebral changes remains unclear. We studied whether vascular and left ventricular (LV) functions are associated with measures of cerebral small vessel disease (cSVD) in the middle-aged general population. METHODS In this cross-sectional analysis of the UK Biobank, 4366 participants (54% female, mean age 61 years) underwent magnetic resonance imaging to assess LV function (ejection fraction [EF] and cardiac index [CI]) and cSVD measures (total brain volume, grey and white matter volumes, hippocampal volume and white matter hyperintensities [WMH]). Augmentation index (AIx) was used as a measure of arterial stiffness. Linear and non-linear associations were evaluated using cardiovascular function measures as determinants and cSVD measures as outcomes. RESULTS EF was non-linearly associated with total brain volume and grey matter volume, with the largest brain volume for an EF between 55 and 60% (both p < 0.001). EF showed a negative linear association with WMH (- 0.23% [- 0.44; - 0.02], p = 0.03), yet no associations were found with white matter or hippocampal volume. CI showed a positive linear association with white matter (β 3194 mm3 [760; 5627], p = 0.01) and hippocampal volume (β 72.5 mm3 [23.0; 122.0], p = 0.004). No associations were found for CI with total brain volume, grey matter volume or WMH. No significant associations were found between AIx and cSVD measures. CONCLUSIONS This study provides novel insights into the complex associations between the heart and the brain, which could potentially guide early interventions aimed at improving cardiovascular function and the prevention of cSVD. KEY POINTS • Ejection fraction is non-linearly and cardiac index is linearly associated with MRI-derived measures of cerebral small vessel disease. • No associations were found for arterial stiffness with cSVD measures.
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15
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Schaeffer MJ, Chan L, Barber PA. The neuroimaging of neurodegenerative and vascular disease in the secondary prevention of cognitive decline. Neural Regen Res 2021; 16:1490-1499. [PMID: 33433462 PMCID: PMC8323688 DOI: 10.4103/1673-5374.303011] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Structural brain changes indicative of dementia occur up to 20 years before the onset of clinical symptoms. Efforts to modify the disease process after the onset of cognitive symptoms have been unsuccessful in recent years. Thus, future trials must begin during the preclinical phases of the disease before symptom onset. Age related cognitive decline is often the result of two coexisting brain pathologies: Alzheimer’s disease (amyloid, tau, and neurodegeneration) and vascular disease. This review article highlights some of the common neuroimaging techniques used to visualize the accumulation of neurodegenerative and vascular pathologies during the preclinical stages of dementia such as structural magnetic resonance imaging, positron emission tomography, and white matter hyperintensities. We also describe some emerging neuroimaging techniques such as arterial spin labeling, diffusion tensor imaging, and quantitative susceptibility mapping. Recent literature suggests that structural imaging may be the most sensitive and cost-effective marker to detect cognitive decline, while molecular positron emission tomography is primarily useful for detecting disease specific pathology later in the disease process. Currently, the presence of vascular disease on magnetic resonance imaging provides a potential target for optimizing vascular risk reduction strategies, and the presence of vascular disease may be useful when combined with molecular and metabolic markers of neurodegeneration for identifying the risk of cognitive impairment.
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Affiliation(s)
- Morgan J Schaeffer
- Department of Clinical Neurosciences, University of Calgary, Calgary, AB, Canada
| | - Leona Chan
- Department of Clinical Neurosciences, University of Calgary, Calgary, AB, Canada
| | - Philip A Barber
- Department of Clinical Neurosciences, University of Calgary, Calgary, AB, Canada
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16
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White matter hyperintensities and risks of cognitive impairment and dementia: A systematic review and meta-analysis of 36 prospective studies. Neurosci Biobehav Rev 2020; 120:16-27. [PMID: 33188821 DOI: 10.1016/j.neubiorev.2020.11.007] [Citation(s) in RCA: 105] [Impact Index Per Article: 26.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2020] [Revised: 10/20/2020] [Accepted: 11/06/2020] [Indexed: 12/16/2022]
Abstract
BACKGROUND White matter hyperintensities of presumed vascular origin (WMH) are one of the imaging features of cerebral small vessel disease. Controversies persist about the effects of WMH on cognitive dysfunction. This meta-analysis aimed to identify the associations of WMH with risks of cognitive impairment and dementia. METHODS We searched PubMed, EMBASE and Cochrane Library for prospective studies. Primary analyses of cognitive dysfunction and sub-analyses of specific outcomes and study characteristics were conducted using random-effect models. RESULTS Thirty-six prospective studies with 19,040 participants were included. WMH at baseline conferred a 14 % elevated risk of cognitive impairment and all-cause dementia (ACD). WMH also conferred 25 % elevated risk of Alzheimer's disease and 73 % elevated risk of vascular dementia. Risk effects of high-grade WMH and continually increasing WMH (in volume or severity) on ACD were revealed. Periventricular WMH conferred a 1.51-fold excess risk for dementia. CONCLUSIONS WMH were associated with increased risk of cognitive dysfunction and could become a neuroimaging indicator of dementia.
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17
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Johnson AC, Miller JE, Cipolla MJ. Memory impairment in spontaneously hypertensive rats is associated with hippocampal hypoperfusion and hippocampal vascular dysfunction. J Cereb Blood Flow Metab 2020; 40:845-859. [PMID: 31088235 PMCID: PMC7168795 DOI: 10.1177/0271678x19848510] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/14/2023]
Abstract
We investigated the effect of chronic hypertension on hippocampal arterioles (HippAs) and hippocampal perfusion as underlying mechanisms of memory impairment, and how large artery stiffness relates to HippA remodeling. Using male spontaneously hypertensive rats (SHR) and normotensive Wistar rats (n = 12/group), long-term (LTM) and spatial memory were tested using object recognition and spontaneous alternation tasks. Hippocampal blood flow was measured via hydrogen clearance basally and during hypercapnia. Reactivity of isolated and pressurized HippAs to pressure and pharmacological activators and inhibitors was investigated. To determine large artery stiffness, distensibility and elastin content were measured in thoracic aorta. SHR had impaired LTM and spatial memory associated with decreased basal blood flow (68 ± 12 mL/100 g/min) vs. Wistar (111 ± 28 mL/100 g/min, p < 0.01) that increased during hypercapnia similarly between groups. Compared to Wistar, HippAs from SHR had increased tone at 60 mmHg (58 ± 9% vs. 37 ± 7%, p < 0.01), and decreased reactivity to small- and intermediate-conductance calcium-activated potassium (SK/IK) channel activation. HippAs in both groups were unaffected by NOS inhibition. Decreased elastin content correlated with increased stiffness in aorta of SHR that was associated with increased stiffness and hypertrophic remodeling of HippAs. Hippocampal vascular dysfunction during hypertension could potentiate memory deficits and may provide a therapeutic target to limit vascular cognitive impairment.
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Affiliation(s)
- Abbie C Johnson
- Department of Neurological Sciences, University of Vermont Larner College of Medicine, Burlington, VT, USA
| | - Justin E Miller
- Department of Neurological Sciences, University of Vermont Larner College of Medicine, Burlington, VT, USA
| | - Marilyn J Cipolla
- Department of Neurological Sciences, University of Vermont Larner College of Medicine, Burlington, VT, USA.,Department of Obstetrics, Gynecology, and Reproductive Sciences, University of Vermont Larner College of Medicine, Burlington, VT, USA.,Department of Pharmacology, University of Vermont Larner College of Medicine, Burlington, VT, USA
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18
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White matter hyperintensities are associated with falls in older people with dementia. Brain Imaging Behav 2020; 13:1265-1272. [PMID: 30145714 DOI: 10.1007/s11682-018-9943-8] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/28/2022]
Abstract
White Matter Hyperintensities (WMHs) are associated with impaired gait, balance and cognition and increased fall risk in cognitively healthy older people. However, few studies have examined such relationships in older people with dementia. Understanding the role of WMHs in falls may assist in developing effective fall prevention strategies. We investigated the relationship between baseline WMHs, cognitive and sensorimotor function and prospective falls in older people with dementia. Twenty-eight community-dwelling older people with mild-moderate dementia (MMSE 11-23; ACE-R < 83) underwent magnetic resonance imaging and assessment of sensorimotor and cognitive (global and processing speed) function at baseline. WMHs, were quantified using a fully automated segmentation toolbox, UBO Detector ( https://cheba.unsw.edu.au/group/neuroimaging-pipeline ). Falls were ascertained prospectively for 12-months using monthly calendars with the assistance of carers. The median age of the participants was 83 years (IQR 77-86); 36% were female; 21 (75%) fell during follow-up. Using Generalized Linear Models, larger volumes of total WMHs were found to be significantly associated with poorer global cognitive and sensorimotor function. Using modified Poisson regression, total, periventricular and deep WMHs were each associated with future falls while controlling for age, sex, intracranial volume and vascular risk. Each standard deviation increase in total and periventricular WMH volume resulted in a 33% (RR 1.33 95%CI 1.07-1.66) and 30% (RR 1.30 95%CI 1.06-1.60) increased risk of falling, respectively. When the deep WMH volume z-scores were dichotomized at the median, individuals with greater deep WMH volumes had an 81% (RR 1.81 95% CI 1.02-3.21) increased risk of falling. WMHs were associated with poorer sensorimotor and cognitive function in people with dementia and total, periventricular and deep WMHs were associated with falls. Further research is needed to confirm these preliminary findings and explore the impact of vascular risk reduction strategies on WMHs, functional performance and falls.
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Smith EE, Biessels GJ, De Guio F, de Leeuw FE, Duchesne S, Düring M, Frayne R, Ikram MA, Jouvent E, MacIntosh BJ, Thrippleton MJ, Vernooij MW, Adams H, Backes WH, Ballerini L, Black SE, Chen C, Corriveau R, DeCarli C, Greenberg SM, Gurol ME, Ingrisch M, Job D, Lam BY, Launer LJ, Linn J, McCreary CR, Mok VC, Pantoni L, Pike GB, Ramirez J, Reijmer YD, Romero JR, Ropele S, Rost NS, Sachdev PS, Scott CJ, Seshadri S, Sharma M, Sourbron S, Steketee RM, Swartz RH, van Oostenbrugge R, van Osch M, van Rooden S, Viswanathan A, Werring D, Dichgans M, Wardlaw JM. Harmonizing brain magnetic resonance imaging methods for vascular contributions to neurodegeneration. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2019; 11:191-204. [PMID: 30859119 PMCID: PMC6396326 DOI: 10.1016/j.dadm.2019.01.002] [Citation(s) in RCA: 53] [Impact Index Per Article: 10.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
INTRODUCTION Many consequences of cerebrovascular disease are identifiable by magnetic resonance imaging (MRI), but variation in methods limits multicenter studies and pooling of data. The European Union Joint Program on Neurodegenerative Diseases (EU JPND) funded the HARmoNizing Brain Imaging MEthodS for VaScular Contributions to Neurodegeneration (HARNESS) initiative, with a focus on cerebral small vessel disease. METHODS Surveys, teleconferences, and an in-person workshop were used to identify gaps in knowledge and to develop tools for harmonizing imaging and analysis. RESULTS A framework for neuroimaging biomarker development was developed based on validating repeatability and reproducibility, biological principles, and feasibility of implementation. The status of current MRI biomarkers was reviewed. A website was created at www.harness-neuroimaging.org with acquisition protocols, a software database, rating scales and case report forms, and a deidentified MRI repository. CONCLUSIONS The HARNESS initiative provides resources to reduce variability in measurement in MRI studies of cerebral small vessel disease.
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Affiliation(s)
- Eric E. Smith
- Department of Clinical Neurosciences, University of Calgary, Calgary, Alberta, Canada
- Department of Radiology, University of Calgary, Calgary, Alberta, Canada
- Hotchkiss Brain Institute, University of Calgary, Alberta, Canada
| | - Geert Jan Biessels
- Department of Neurology, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, Netherlands
| | - François De Guio
- Department of Neurology, Lariboisière Hospital, University Paris Diderot, Paris, France
| | - Frank Erik de Leeuw
- Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Donders Center for Medical Neuroscience, Radboud University Medical Center, Nijmegen, Netherlands
| | - Simon Duchesne
- CERVO Research Center, Quebec Mental Health Institute, Québec, Canada
- Radiology Department, Université Laval, Québec, Canada
| | - Marco Düring
- Institute for Stroke and Dementia Research (ISD), University Hospital, Ludwig-Maximilians-Universität LMU, Munich, Germany
- German Center for Neurodegenerative Diseases (DZNE, Munich), Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Richard Frayne
- Department of Clinical Neurosciences, University of Calgary, Calgary, Alberta, Canada
- Department of Radiology, University of Calgary, Calgary, Alberta, Canada
- Hotchkiss Brain Institute, University of Calgary, Alberta, Canada
- Seaman Family MR Centre, Foothills Medical Centre, Calgary, Alberta, Canada
| | - M. Arfan Ikram
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, Netherlands
| | - Eric Jouvent
- Department of Neurology, Lariboisière Hospital, University Paris Diderot, Paris, France
| | - Bradley J. MacIntosh
- Heart and Stroke Foundation Canadian Partnership for Stroke Recovery, Department of Medical Biophysics, Sunnybrook Research Institute, University of Toronto, Ontario, Canada
| | - Michael J. Thrippleton
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK
- UK Dementia Research Institute, University of Edinburgh, Edinburgh, UK
| | - Meike W. Vernooij
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, Netherlands
- Department of Radiology and Nuclear Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Hieab Adams
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, Netherlands
- Department of Radiology and Nuclear Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Walter H. Backes
- Department of Radiology & Nuclear Medicine, School for Mental Health & Neuroscience, Maastricht University Medical Center, Maastricht, The Netherlands
| | - Lucia Ballerini
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK
- UK Dementia Research Institute, University of Edinburgh, Edinburgh, UK
| | - Sandra E. Black
- Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, University of Toronto, Toronto, Ontario, Canada
- Heart and Stroke Foundation Canadian Partnership for Stroke Recovery, Toronto, Ontario, Canada
- Department of Medicine (Neurology), Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Ontario, Canada
| | - Christopher Chen
- Memory Aging and Cognition Centre, Department of Pharmacology, National University of Singapore, Singapore
| | - Rod Corriveau
- National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA
| | - Charles DeCarli
- Department of Neurology and Center for Neuroscience, University of California at Davis, Davis, CA, USA
| | - Steven M. Greenberg
- J. Philip Kistler Stroke Research Center, Stroke Service and Memory Disorders Unit, Massachusetts General Hospital, Boston, MA, USA
| | - M. Edip Gurol
- J. Philip Kistler Stroke Research Center, Stroke Service and Memory Disorders Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Michael Ingrisch
- Department of Radiology, Ludwig-Maximilians-University Hospital Munich, Munich, Germany
| | - Dominic Job
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK
- UK Dementia Research Institute, University of Edinburgh, Edinburgh, UK
| | - Bonnie Y.K. Lam
- Therese Pei Fong Chow Research Centre for Prevention of Dementia, Gerald Choa Neuroscience Centre, Lui Che Woo Institute of Innovative Medicine, Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong
| | - Lenore J. Launer
- National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
| | - Jennifer Linn
- Institute of Neuroradiology, University Hospital Carl Gustav Carus, Dresden, Germany
| | - Cheryl R. McCreary
- Department of Clinical Neurosciences, University of Calgary, Calgary, Alberta, Canada
- Department of Radiology, University of Calgary, Calgary, Alberta, Canada
- Seaman Family MR Centre, Foothills Medical Centre, Calgary, Alberta, Canada
| | - Vincent C.T. Mok
- Therese Pei Fong Chow Research Centre for Prevention of Dementia, Gerald Choa Neuroscience Centre, Lui Che Woo Institute of Innovative Medicine, Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong
| | - Leonardo Pantoni
- Luigi Sacco Department of Biomedical and Clinical Sciences, University of Milan, Milan, Italy
| | - G. Bruce Pike
- Department of Clinical Neurosciences, University of Calgary, Calgary, Alberta, Canada
- Department of Radiology, University of Calgary, Calgary, Alberta, Canada
- Hotchkiss Brain Institute, University of Calgary, Alberta, Canada
| | - Joel Ramirez
- Heart and Stroke Foundation Canadian Partnership for Stroke Recovery, Department of Medical Biophysics, Sunnybrook Research Institute, University of Toronto, Ontario, Canada
- Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, University of Toronto, Toronto, Ontario, Canada
| | - Yael D. Reijmer
- Department of Neurology, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, Netherlands
| | - Jose Rafael Romero
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
- Framingham Heart Study, Framingham, MA, USA
| | - Stefan Ropele
- Department of Neurology, Medical University of Graz, Graz, Austria
| | - Natalia S. Rost
- J. Philip Kistler Stroke Research Center, Massachusetts General Hospital, Boston, MA, USA
| | - Perminder S. Sachdev
- Centre for Healthy Brain Ageing, University of New South Wales, Sydney, Australia
| | - Christopher J.M. Scott
- Heart and Stroke Foundation Canadian Partnership for Stroke Recovery, Department of Medical Biophysics, Sunnybrook Research Institute, University of Toronto, Ontario, Canada
- Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, University of Toronto, Toronto, Ontario, Canada
| | - Sudha Seshadri
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX, USA
| | - Mukul Sharma
- Population Health Research Institute, Hamilton, Ontario, Canada
- Department of Medicine (Neurology) McMaster University, Hamilton, Ontario, Canada
| | - Steven Sourbron
- Imaging Biomarkers Group, Department of Biomedical Imaging Sciences, University of Leeds, Leeds, UK
| | - Rebecca M.E. Steketee
- Department of Radiology and Nuclear Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Richard H. Swartz
- Department of Medicine (Neurology), University of Toronto, Toronto, Canada
- Hurvitz Brain Sciences Program, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Canada
| | - Robert van Oostenbrugge
- Department of Neurology, School for Mental Health and Neuroscience, Maastricht University Medical Center, Maastricht, the Netherlands
| | - Matthias van Osch
- C.J. Gorter Center for high field MRI, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Sanneke van Rooden
- Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Anand Viswanathan
- J. Philip Kistler Stroke Research Center, Stroke Service and Memory Disorders Unit, Massachusetts General Hospital, Boston, MA, USA
| | - David Werring
- University College London Queen Square institute of Neurology, London, UK
| | - Martin Dichgans
- Institute for Stroke and Dementia Research (ISD), University Hospital, Ludwig-Maximilians-Universität LMU, Munich, Germany
- German Center for Neurodegenerative Diseases (DZNE, Munich), Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Joanna M. Wardlaw
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK
- UK Dementia Research Institute, University of Edinburgh, Edinburgh, UK
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Debette S, Schilling S, Duperron MG, Larsson SC, Markus HS. Clinical Significance of Magnetic Resonance Imaging Markers of Vascular Brain Injury: A Systematic Review and Meta-analysis. JAMA Neurol 2019; 76:81-94. [PMID: 30422209 DOI: 10.1001/jamaneurol.2018.3122] [Citation(s) in RCA: 354] [Impact Index Per Article: 70.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Importance Covert vascular brain injury (VBI) is highly prevalent in community-dwelling older persons, but its clinical and therapeutic implications are debated. Objective To better understand the clinical significance of VBI to optimize prevention strategies for the most common age-related neurological diseases, stroke and dementia. Data Source We searched for articles in PubMed between 1966 and December 22, 2017, studying the association of 4 magnetic resonance imaging (MRI) markers of covert VBI (white matter hyperintensities [WMHs] of presumed vascular origin, MRI-defined covert brain infarcts [BIs], cerebral microbleeds [CMBs], and perivascular spaces [PVSs]) with incident stroke, dementia, or death. Study Selection Data were taken from prospective, longitudinal cohort studies including 50 or more adults. Data Extraction and Synthesis We performed inverse variance-weighted meta-analyses with random effects and z score-based meta-analyses for WMH burden. The significance threshold was P < .003 (17 independent tests). We complied with the Meta-analyses of Observational Studies in Epidemiology guidelines. Main Outcomes and Measures Stroke (hemorrhagic and ischemic), dementia (all and Alzheimer disease), and death. Results Of 2846 articles identified, 94 studies were eligible, with up to 14 529 participants for WMH, 16 012 participants for BI, 15 693 participants for CMB, and 4587 participants for PVS. Extensive WMH burden was associated with higher risk of incident stroke (hazard ratio [HR], 2.45; 95% CI, 1.93-3.12; P < .001), ischemic stroke (HR, 2.39; 95% CI, 1.65-3.47; P < .001), intracerebral hemorrhage (HR, 3.17; 95% CI, 1.54-6.52; P = .002), dementia (HR, 1.84; 95% CI, 1.40-2.43; P < .001), Alzheimer disease (HR, 1.50; 95% CI, 1.22-1.84; P < .001), and death (HR, 2.00; 95% CI, 1.69-2.36; P < .001). Presence of MRI-defined BIs was associated with higher risk of incident stroke (HR, 2.38; 95% CI, 1.87-3.04; P < .001), ischemic stroke (HR, 2.18; 95% CI, 1.67-2.85; P < .001), intracerebral hemorrhage (HR, 3.81; 95% CI, 1.75-8.27; P < .001), and death (HR, 1.64; 95% CI, 1.40-1.91; P < .001). Presence of CMBs was associated with increased risk of stroke (HR, 1.98; 95% CI, 1.55-2.53; P < .001), ischemic stroke (HR, 1.92; 95% CI, 1.40-2.63; P < .001), intracerebral hemorrhage (HR, 3.82; 95% CI, 2.15-6.80; P < .001), and death (HR, 1.53; 95% CI, 1.31-1.80; P < .001). Data on PVS were limited and insufficient to conduct meta-analyses but suggested an association of high PVS burden with increased risk of stroke, dementia, and death; this requires confirmation. Conclusions and Relevance We report evidence that MRI markers of VBI have major clinical significance. This research prompts careful evaluation of the benefit-risk ratio for available prevention strategies in individuals with covert VBI.
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Affiliation(s)
- Stéphanie Debette
- University of Bordeaux, Inserm 1219, Bordeaux Population Health Research Center, Bordeaux, France.,Department of Neurology, Memory Clinic, Bordeaux University Hospital, Bordeaux, France
| | - Sabrina Schilling
- University of Bordeaux, Inserm 1219, Bordeaux Population Health Research Center, Bordeaux, France
| | - Marie-Gabrielle Duperron
- University of Bordeaux, Inserm 1219, Bordeaux Population Health Research Center, Bordeaux, France
| | - Susanna C Larsson
- Stroke Research Group, Department of Clinical Neurosciences, University of Cambridge, Cambridge Biomedical Campus, Cambridge, United Kingdom.,Unit of Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Hugh S Markus
- Stroke Research Group, Department of Clinical Neurosciences, University of Cambridge, Cambridge Biomedical Campus, Cambridge, United Kingdom
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21
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Marebwa BK, Adams RJ, Magwood GS, Basilakos A, Mueller M, Rorden C, Fridriksson J, Bonilha L. Cardiovascular Risk Factors and Brain Health: Impact on Long-Range Cortical Connections and Cognitive Performance. J Am Heart Assoc 2019; 7:e010054. [PMID: 30520672 PMCID: PMC6405561 DOI: 10.1161/jaha.118.010054] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Background Cardiovascular risk factor burden in the absence of clinical or radiological "events" is associated with mild cognitive impairment. Magnetic resonance imaging techniques exploring the integrity of neuronal fiber connectivity within white matter networks supporting cognitive processing could be used to measure the impact of cardiovascular disease on brain health and be used beyond bedside neuropsychological tests to detect subclinical changes and select or stratify participants for entry into clinical trials. Methods and Results We assessed the relationship between verbal IQ and brain network integrity and the effect of cardiovascular risk factors on network integrity by constructing whole-brain structural connectomes from magnetic resonance imaging diffusion images (N=60) from people with various degrees of cardiovascular risk factor burden. We measured axonal integrity by calculating network density and determined the effect of fiber loss on network topology and efficiency, using graph theory. Multivariate analyses were used to evaluate the relationship between cardiovascular risk factor burden, physical activity, age, education, white matter integrity, and verbal IQ . Reduced network density, resulting from a disproportionate loss of long-range white matter fibers, was associated with white matter network fragmentation ( r=-0.52, P<10-4), lower global efficiency ( r=0.91, P<10-20), and decreased verbal IQ (adjusted R2=0.23, P<10-4). Conclusions Cardiovascular risk factors may mediate negative effects on brain health via loss of energy-dependent long-range white matter fibers, which in turn leads to disruption of the topological organization of the white matter networks, lowered efficiency, and reduced cognitive function.
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Affiliation(s)
- Barbara K Marebwa
- 1 Department of Neurology Medical University of South Carolina Charleston SC
| | - Robert J Adams
- 1 Department of Neurology Medical University of South Carolina Charleston SC
| | - Gayenell S Magwood
- 2 Department of Nursing Medical University of South Carolina Charleston SC
| | - Alexandra Basilakos
- 3 Department of Communication Sciences and Disorders University of South Carolina Columbia SC
| | - Martina Mueller
- 2 Department of Nursing Medical University of South Carolina Charleston SC
| | - Chris Rorden
- 4 Department of Psychology University of South Carolina Columbia SC
| | - Julius Fridriksson
- 3 Department of Communication Sciences and Disorders University of South Carolina Columbia SC
| | - Leonardo Bonilha
- 1 Department of Neurology Medical University of South Carolina Charleston SC
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22
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Power MC, Su D, Wu A, Reid RI, Jack CR, Knopman DS, Coresh J, Huang J, Kantarci K, Sharrett AR, Gottesman RG, Griswold ME, Mosley TH. Association of white matter microstructural integrity with cognition and dementia. Neurobiol Aging 2019; 83:63-72. [PMID: 31585368 PMCID: PMC6914220 DOI: 10.1016/j.neurobiolaging.2019.08.021] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2019] [Revised: 08/07/2019] [Accepted: 08/21/2019] [Indexed: 10/26/2022]
Abstract
Late-life measures of white matter (WM) microstructural integrity may predict cognitive status, cognitive decline, and incident mild cognitive impairment (MCI) or dementia. We considered participants of the Atherosclerosis Risk in Communities study who underwent cognitive assessment and neuroimaging in 2011-2013 and were followed through 2016-2017 (n = 1775 for analyses of prevalent MCI and dementia, baseline cognitive performance, and longitudinal cognitive change and n = 889 for analyses of incident MCI, dementia, or death). Cross-sectionally, both overall WM fractional anisotropy and overall WM mean diffusivity were strongly associated with baseline cognitive performance and risk of prevalent MCI or dementia. Longitudinally, greater overall WM mean diffusivity was associated with accelerated cognitive decline, as well as incident MCI, incident dementia, and mortality, but WM fractional anisotropy was not robustly associated with cognitive change or incident cognitive impairment. Both cross-sectional and longitudinal associations were attenuated after additionally adjusting for likely downstream pathologic changes. Increased WM mean diffusivity may provide an early indication of dementia pathogenesis.
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Affiliation(s)
- Melinda C Power
- Department of Epidemiology and Biostatistics, Milken Institute School of Public Health, George Washington University, Washington, DC, USA.
| | - Dan Su
- Department of Data Science, JD Bower School of Population Health, University of Mississippi Medical Center, Jackson, MS, USA
| | - Aozhou Wu
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Robert I Reid
- Department of Information Technology, Mayo Clinic, Rochester, MN, USA
| | | | | | - Joe Coresh
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Juebin Huang
- Department of Neurology, University of Mississippi Medical Center, Jackson, MS, USA
| | - Kejal Kantarci
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | - A Richey Sharrett
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Rebecca G Gottesman
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA; Department of Neurology, Johns Hopkins University, Baltimore, MD, USA
| | - Mike E Griswold
- Department of Data Science, JD Bower School of Population Health, University of Mississippi Medical Center, Jackson, MS, USA
| | - Thomas H Mosley
- Department of Neurology, University of Mississippi Medical Center, Jackson, MS, USA; Department of Geriatrics, University of Mississippi Medical Center, Jackson, MS, USA
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Longitudinal changes in rich club organization and cognition in cerebral small vessel disease. NEUROIMAGE-CLINICAL 2019; 24:102048. [PMID: 31706220 PMCID: PMC6978216 DOI: 10.1016/j.nicl.2019.102048] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/24/2019] [Revised: 09/11/2019] [Accepted: 10/21/2019] [Indexed: 01/06/2023]
Abstract
Cerebral small vessel disease (SVD) is considered the most important vascular contributor to the development of cognitive impairment and dementia. There is increasing awareness that SVD exerts its clinical effects by disrupting white matter connections, predominantly disrupting connections between rich club nodes, a set of highly connected and interconnected regions. Here we examined the progression of disturbances in rich club organization in older adults with SVD and their associations with conventional SVD markers and cognitive decline. We additionally investigated associations of baseline network measures with dementia. In 270 participants of the RUN DMC study, we performed diffusion tensor imaging (DTI) and cognitive assessments longitudinally. Rich club organization was examined in structural networks derived from DTI followed by deterministic tractography. Global efficiency (p<0.05) and strength of rich club connections (p<0.001) declined during follow-up. Decline in strength of peripheral connections was associated with a decline in overall cognition (β=0.164; p<0.01), psychomotor speed (β=0.151; p<0.05) and executive function (β=0.117; p<0.05). Baseline network measures were reduced in participants with dementia, and the association between WMH and dementia was causally mediated by global efficiency (p = =0.037) and peripheral connection strength (p = =0.040). SVD-related disturbances in rich club organization progressed over time, predominantly in participants with severe SVD. In this study, we found no specific role of rich club connectivity disruption in causing cognitive decline or dementia. The effect of WMH on dementia was mediated by global network efficiency and the strength of peripheral connections, suggesting an important role for network disruption in causing cognitive decline and dementia in older adults with SVD.
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Abstract
Small vessel disease (SVD) refers to conditions where damage to arterioles and capillaries is predominant, leading to reduced, or interrupted perfusion of the affected organ. Data suggest that when this condition is evident in any organ, it is already systemic in its occurrence and consequences. SVD affects primarily organs that receive significant portions of cardiac output such as the brain, the kidney, and the retina. Thus, SVD is a major etiologic cause in debilitating conditions such as renal failure, blindness, lacunar infarcts, and dementia. The factors that lead to this devastating condition include all the known vascular risk factors when they are not strictly controlled, but lifestyles that include sedentary existence, obesity, and poor sleep patterns are also recognized drivers of SVD. In addition, depression is now recognized as a vascular risk factor. Inflammation is a mediator of SVD, but it is not known which factor(s) predominate in its etiology. This article emphasizes the need for more investigations to define this link further and suggests clinical and societal responses that might reduce the major impacts of this condition on populations.
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Affiliation(s)
- Antoine M Hakim
- Ottawa Hospital Research Institute, Ottawa, ON, Canada.,Faculty of Medicine, Brain and Mind Research Institute, University of Ottawa, Ottawa, ON, Canada.,Division of Neurology, University of Ottawa, Ottawa, ON, Canada
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25
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Ter Telgte A, van Leijsen EMC, Wiegertjes K, Klijn CJM, Tuladhar AM, de Leeuw FE. Cerebral small vessel disease: from a focal to a global perspective. Nat Rev Neurol 2019; 14:387-398. [PMID: 29802354 DOI: 10.1038/s41582-018-0014-y] [Citation(s) in RCA: 287] [Impact Index Per Article: 57.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Abstract
Cerebral small vessel disease (SVD) is commonly observed on neuroimaging among elderly individuals and is recognized as a major vascular contributor to dementia, cognitive decline, gait impairment, mood disturbance and stroke. However, clinical symptoms are often highly inconsistent in nature and severity among patients with similar degrees of SVD on brain imaging. Here, we provide a new framework based on new advances in structural and functional neuroimaging that aims to explain the remarkable clinical variation in SVD. First, we discuss the heterogeneous pathology present in SVD lesions despite an identical appearance on imaging and the perilesional and remote effects of these lesions. We review effects of SVD on structural and functional connectivity in the brain, and we discuss how network disruption by SVD can lead to clinical deficits. We address reserve and compensatory mechanisms in SVD and discuss the part played by other age-related pathologies. Finally, we conclude that SVD should be considered a global rather than a focal disease, as the classically recognized focal lesions affect remote brain structures and structural and functional network connections. The large variability in clinical symptoms among patients with SVD can probably be understood by taking into account the heterogeneity of SVD lesions, the effects of SVD beyond the focal lesions, the contribution of neurodegenerative pathologies other than SVD, and the interaction with reserve mechanisms and compensatory mechanisms.
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Affiliation(s)
- Annemieke Ter Telgte
- Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Donders Centre for Medical Neuroscience, Radboud University Medical Center, Nijmegen, Netherlands
| | - Esther M C van Leijsen
- Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Donders Centre for Medical Neuroscience, Radboud University Medical Center, Nijmegen, Netherlands
| | - Kim Wiegertjes
- Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Donders Centre for Medical Neuroscience, Radboud University Medical Center, Nijmegen, Netherlands
| | - Catharina J M Klijn
- Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Donders Centre for Medical Neuroscience, Radboud University Medical Center, Nijmegen, Netherlands
| | - Anil M Tuladhar
- Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Donders Centre for Medical Neuroscience, Radboud University Medical Center, Nijmegen, Netherlands
| | - Frank-Erik de Leeuw
- Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Donders Centre for Medical Neuroscience, Radboud University Medical Center, Nijmegen, Netherlands.
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26
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Arnoldussen IAC, Gustafson DR, Leijsen EMC, de Leeuw FE, Kiliaan AJ. Adiposity is related to cerebrovascular and brain volumetry outcomes in the RUN DMC study. Neurology 2019; 93:e864-e878. [PMID: 31363056 DOI: 10.1212/wnl.0000000000008002] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2018] [Accepted: 04/08/2019] [Indexed: 01/07/2023] Open
Abstract
OBJECTIVE Adiposity predictors, body mass index (BMI), waist circumference (WC), and blood leptin and total adiponectin levels were associated with components of cerebral small vessel disease (CSVD) and brain volumetry in 503 adults with CSVD who were ≥50 years of age and enrolled in the Radboud University Nijmegen Diffusion Tensor and Magnetic Resonance Imaging Cohort (RUN DMC). METHODS RUN DMC participants were followed up for 9 years (2006-2015). BMI, WC, brain imaging, and dementia diagnoses were evaluated at baseline and follow-up. Adipokines were measured at baseline. Brain imaging outcomes included CSVD components, white matter hyperintensities, lacunes, microbleeds, gray and white matter, hippocampal, total brain, and intracranial volumes. RESULTS Cross-sectionally among men at baseline, higher BMI, WC, and leptin were associated with lower gray matter and total brain volumes, and higher BMI and WC were associated with lower hippocampal volume. At follow-up 9 years later, higher BMI was cross-sectionally associated with lower gray matter volume, and an obese WC (>102 cm) was protective for ≥1 lacune or ≥1 microbleed in men. In women, increasing BMI and overweight or obesity (BMI ≥25 kg/m2 or WC >88 cm) were associated with ≥1 lacune. Longitudinally, over 9 years, a baseline obese WC was associated with decreasing hippocampal volume, particularly in men, and increasing white matter hyperintensity volume in women and men. CONCLUSIONS Anthropometric and metabolic adiposity predictors were differentially associated with CSVD components and brain volumetry outcomes by sex. Higher adiposity is associated with a vascular-neurodegenerative spectrum among adults at risk for vascular forms of cognitive impairment and dementias.
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Affiliation(s)
- Ilse A C Arnoldussen
- From the Departments of Anatomy (I.A.C.A., A.J.K.) and Neurology (E.M.C.L., F.-E.d.L.), Donders Institute for Brain, Cognition and Behaviour, and Radboud Alzheimer Center (I.A.C.A., A.J.K.), Radboud University Medical Center, Nijmegen, the Netherlands; Department of Neurology (D.R.G.), The State University of New York Downstate Health Sciences University, Brooklyn; and Department of Health and Education (D.R.G.), University of Skövde, Sweden
| | - Deborah R Gustafson
- From the Departments of Anatomy (I.A.C.A., A.J.K.) and Neurology (E.M.C.L., F.-E.d.L.), Donders Institute for Brain, Cognition and Behaviour, and Radboud Alzheimer Center (I.A.C.A., A.J.K.), Radboud University Medical Center, Nijmegen, the Netherlands; Department of Neurology (D.R.G.), The State University of New York Downstate Health Sciences University, Brooklyn; and Department of Health and Education (D.R.G.), University of Skövde, Sweden.
| | - Esther M C Leijsen
- From the Departments of Anatomy (I.A.C.A., A.J.K.) and Neurology (E.M.C.L., F.-E.d.L.), Donders Institute for Brain, Cognition and Behaviour, and Radboud Alzheimer Center (I.A.C.A., A.J.K.), Radboud University Medical Center, Nijmegen, the Netherlands; Department of Neurology (D.R.G.), The State University of New York Downstate Health Sciences University, Brooklyn; and Department of Health and Education (D.R.G.), University of Skövde, Sweden
| | - Frank-Erik de Leeuw
- From the Departments of Anatomy (I.A.C.A., A.J.K.) and Neurology (E.M.C.L., F.-E.d.L.), Donders Institute for Brain, Cognition and Behaviour, and Radboud Alzheimer Center (I.A.C.A., A.J.K.), Radboud University Medical Center, Nijmegen, the Netherlands; Department of Neurology (D.R.G.), The State University of New York Downstate Health Sciences University, Brooklyn; and Department of Health and Education (D.R.G.), University of Skövde, Sweden
| | - Amanda J Kiliaan
- From the Departments of Anatomy (I.A.C.A., A.J.K.) and Neurology (E.M.C.L., F.-E.d.L.), Donders Institute for Brain, Cognition and Behaviour, and Radboud Alzheimer Center (I.A.C.A., A.J.K.), Radboud University Medical Center, Nijmegen, the Netherlands; Department of Neurology (D.R.G.), The State University of New York Downstate Health Sciences University, Brooklyn; and Department of Health and Education (D.R.G.), University of Skövde, Sweden
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27
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Charidimou A, Shams S, Romero JR, Ding J, Veltkamp R, Horstmann S, Eiriksdottir G, van Buchem MA, Gudnason V, Himali J, Gurol ME, Viswanathan A, Imaizumi T, Vernooij MW, Seshadri S, Greenberg SM, Benavente OR, Launer LJ, Shoamanesh A. Clinical significance of cerebral microbleeds on MRI: A comprehensive meta-analysis of risk of intracerebral hemorrhage, ischemic stroke, mortality, and dementia in cohort studies (v1). Int J Stroke 2018; 13:454-468. [PMID: 29338604 PMCID: PMC6123529 DOI: 10.1177/1747493017751931] [Citation(s) in RCA: 70] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Background Cerebral microbleeds can confer a high risk of intracerebral hemorrhage, ischemic stroke, death and dementia, but estimated risks remain imprecise and often conflicting. We investigated the association between cerebral microbleeds presence and these outcomes in a large meta-analysis of all published cohorts including: ischemic stroke/TIA, memory clinic, "high risk" elderly populations, and healthy individuals in population-based studies. Methods Cohorts (with > 100 participants) that assessed cerebral microbleeds presence on MRI, with subsequent follow-up (≥3 months) were identified. The association between cerebral microbleeds and each of the outcomes (ischemic stroke, intracerebral hemorrhage, death, and dementia) was quantified using random effects models of (a) unadjusted crude odds ratios and (b) covariate-adjusted hazard rations. Results We identified 31 cohorts ( n = 20,368): 19 ischemic stroke/TIA ( n = 7672), 4 memory clinic ( n = 1957), 3 high risk elderly ( n = 1458) and 5 population-based cohorts ( n = 11,722). Cerebral microbleeds were associated with an increased risk of ischemic stroke (OR: 2.14; 95% CI: 1.58-2.89 and adj-HR: 2.09; 95% CI: 1.71-2.57), but the relative increase in future intracerebral hemorrhage risk was greater (OR: 4.65; 95% CI: 2.68-8.08 and adj-HR: 3.93; 95% CI: 2.71-5.69). Cerebral microbleeds were an independent predictor of all-cause mortality (adj-HR: 1.36; 95% CI: 1.24-1.48). In three population-based studies, cerebral microbleeds were independently associated with incident dementia (adj-HR: 1.35; 95% CI: 1.00-1.82). Results were overall consistent in analyses stratified by different populations, but with different degrees of heterogeneity. Conclusions Our meta-analysis shows that cerebral microbleeds predict an increased risk of stroke, death, and dementia and provides up-to-date effect sizes across different clinical settings. These pooled estimates can inform clinical decisions and trials, further supporting cerebral microbleeds role as biomarkers of underlying subclinical brain pathology in research and clinical settings.
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Affiliation(s)
- Andreas Charidimou
- Department of Neurology, Harvard Medical School, J. Philip
Kistler Stroke Research Center, Massachusetts General Hospital, Boston, MA,
USA
- Cochrane Methods, Individual Patient Data Meta-analysis
Group
| | - Sara Shams
- Department of Clinical Science, Intervention, and
Technology, Division of Medical Imaging and Technology, Karolinska Institutet,
Stockholm, Sweden; Department of Radiology, Karolinska University Hospital,
Stockholm, Sweden
| | - Jose R Romero
- Department of Neurology, Boston University School of
Medicine, and the NHLBI’s Framingham Heart Study, Framingham,
Massachusetts
| | - Jie Ding
- Laboratory of Epidemiology and Population Sciences,
National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
| | - Roland Veltkamp
- Department of Neurology, University of Heidelberg,
Heidelberg, Germany
- Department of Stroke Medicine, Division of Brain Sciences,
Imperial College London, London, UK
| | - Solveig Horstmann
- Department of Neurology, University of Heidelberg,
Heidelberg, Germany
| | | | - Mark A van Buchem
- Department of Radiology, Leiden University Medical Center,
Leiden, the Netherlands
| | | | - JayandraJ Himali
- Department of Neurology, Boston University School of
Medicine, and the NHLBI’s Framingham Heart Study, Framingham,
Massachusetts
- Department of Biostatistics, Boston University School of
Public Health, Boston, MA, USA
| | - M Edip Gurol
- Department of Neurology, Harvard Medical School, J. Philip
Kistler Stroke Research Center, Massachusetts General Hospital, Boston, MA,
USA
| | - Anand Viswanathan
- Department of Neurology, Harvard Medical School, J. Philip
Kistler Stroke Research Center, Massachusetts General Hospital, Boston, MA,
USA
| | - Toshio Imaizumi
- Department of Neurosurgery, Kushiro City General
Hospital, Kushiro, Japan
| | - Meike W Vernooij
- Department of Epidemiology and Department of Radiology
and Nuclear Medicine; Erasmus MC University Medical Center, Rotterdam, the
Netherlands
| | - Sudha Seshadri
- Department of Neurology, Boston University School of
Medicine, and the NHLBI’s Framingham Heart Study, Framingham,
Massachusetts
| | - Steven M Greenberg
- Department of Neurology, Harvard Medical School, J. Philip
Kistler Stroke Research Center, Massachusetts General Hospital, Boston, MA,
USA
| | - Oscar R Benavente
- Division of Neurology, Department of Medicine, Stroke and
Cerebrovascular Health Program, University of British Columbia, UBC Hospital,
Vancouver, British Columbia, Canada
| | - Lenore J Launer
- Laboratory of Epidemiology and Population Sciences,
National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
| | - Ashkan Shoamanesh
- Department of Medicine (Neurology), McMaster University
and Population Health Research Institute, Hamilton, Ontario, Canada
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28
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The effect of the total small vessel disease burden on the structural brain network. Sci Rep 2018; 8:7442. [PMID: 29748646 PMCID: PMC5945601 DOI: 10.1038/s41598-018-25917-4] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2018] [Accepted: 05/01/2018] [Indexed: 12/20/2022] Open
Abstract
Different cerebral small vessel disease (SVD) lesion types have been shown to disrupt structural brain network individually. Considering that they often coexist, we investigated the relation between their collective effect using the recently proposed total SVD score and structural brain network on MRI in 95 patients with first transient ischemic attack (TIA) or ischemic stroke. Fifty-nine patients with and 36 without any SVD lesions were included. The total SVD score was recorded. Diffusion tensor imaging was performed to estimate structural brain connections for subsequent brain connectivity analysis. The global efficiency and characteristic path length of the structural brain network are respectively lower and higher due to SVD. Lower nodal efficiency is also found in the insular, precuneus, supplementary motor area, paracentral lobule, putamen and hippocampus. The total SVD score is correlated with global network measures, the local clustering coefficient and nodal efficiency of hippocampus, and the nodal efficiency of paracentral lobule. We have successfully demonstrated that the disruption of global and local structural brain networks are associated with the increase in the overall SVD severity or burden of patients with TIA or first-time stroke.
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29
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Williams OA, Zeestraten EA, Benjamin P, Lambert C, Lawrence AJ, Mackinnon AD, Morris RG, Markus HS, Charlton RA, Barrick TR. Diffusion tensor image segmentation of the cerebrum provides a single measure of cerebral small vessel disease severity related to cognitive change. Neuroimage Clin 2017; 16:330-342. [PMID: 28861335 PMCID: PMC5568143 DOI: 10.1016/j.nicl.2017.08.016] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2017] [Revised: 07/05/2017] [Accepted: 08/12/2017] [Indexed: 02/02/2023]
Abstract
Cerebral small vessel disease (SVD) is the primary cause of vascular cognitive impairment and is associated with decline in executive function (EF) and information processing speed (IPS). Imaging biomarkers are needed that can monitor and identify individuals at risk of severe cognitive decline. Recently there has been interest in combining several magnetic resonance imaging (MRI) markers of SVD into a unitary score to describe disease severity. Here we apply a diffusion tensor image (DTI) segmentation technique (DSEG) to describe SVD related changes in a single unitary score across the whole cerebrum, to investigate its relationship with cognitive change over a three-year period. 98 patients (aged 43-89) with SVD underwent annual MRI scanning and cognitive testing for up to three years. DSEG provides a vector of 16 discrete segments describing brain microstructure of healthy and/or damaged tissue. By calculating the scalar product of each DSEG vector in reference to that of a healthy ageing control we generate an angular measure (DSEG θ) describing the patients' brain tissue microstructural similarity to a disease free model of a healthy ageing brain. Conventional MRI markers of SVD brain change were also assessed including white matter hyperintensities, cerebral atrophy, incident lacunes, cerebral-microbleeds, and white matter microstructural damage measured by DTI histogram parameters. The impact of brain change on cognition was explored using linear mixed-effects models. Post-hoc sample size analysis was used to assess the viability of DSEG θ as a tool for clinical trials. Changes in brain structure described by DSEG θ were related to change in EF and IPS (p < 0.001) and remained significant in multivariate models including other MRI markers of SVD as well as age, gender and premorbid IQ. Of the conventional markers, presence of new lacunes was the only marker to remain a significant predictor of change in EF and IPS in the multivariate models (p = 0.002). Change in DSEG θ was also related to change in all other MRI markers (p < 0.017), suggesting it may be used as a surrogate marker of SVD damage across the cerebrum. Sample size estimates indicated that fewer patients would be required to detect treatment effects using DSEG θ compared to conventional MRI and DTI markers of SVD severity. DSEG θ is a powerful tool for characterising subtle brain change in SVD that has a negative impact on cognition and remains a significant predictor of cognitive change when other MRI markers of brain change are accounted for. DSEG provides an automatic segmentation of the whole cerebrum that is sensitive to a range of SVD related structural changes and successfully predicts cognitive change. Power analysis shows DSEG θ has potential as a monitoring tool in clinical trials. As such it may provide a marker of SVD severity from a single imaging modality (i.e. DTIs).
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Affiliation(s)
- Owen A. Williams
- Neuroscience Research Centre, Molecular and Clinical Sciences Research Institute, St George's University of London, London, UK
| | - Eva A. Zeestraten
- Neuroscience Research Centre, Molecular and Clinical Sciences Research Institute, St George's University of London, London, UK
| | - Philip Benjamin
- Department of Radiology, Charing Cross Hospital Campus, Imperial College NHS Trust, London, UK
| | - Christian Lambert
- Neuroscience Research Centre, Molecular and Clinical Sciences Research Institute, St George's University of London, London, UK
| | - Andrew J. Lawrence
- Stroke Research Group, Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Andrew D. Mackinnon
- Atkinson Morley Regional Neuroscience Centre, St George's NHS Healthcare Trust, London, UK
| | - Robin G. Morris
- Department of Psychology, King's College Institute of Psychiatry, Psychology, and Neuroscience, London, UK
| | - Hugh S. Markus
- Stroke Research Group, Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | | | - Thomas R. Barrick
- Neuroscience Research Centre, Molecular and Clinical Sciences Research Institute, St George's University of London, London, UK
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30
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Johnson AC, Cipolla MJ. Altered hippocampal arteriole structure and function in a rat model of preeclampsia: Potential role in impaired seizure-induced hyperemia. J Cereb Blood Flow Metab 2017; 37:2857-2869. [PMID: 27815419 PMCID: PMC5536792 DOI: 10.1177/0271678x16676287] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
We investigated the effect of experimental preeclampsia on hyperemia during seizure in the hippocampus and vascular function and structure of hippocampal arterioles using Sprague Dawley rats (n = 14/group) that were nonpregnant, pregnant (d20), or had experimental preeclampsia (induced by a high cholesterol diet d7-20). Hyperemia was measured via hydrogen clearance basally and during pentylenetetrazol-induced seizure (40-130 mg/kg i.v.). Reactivity of isolated and pressurized hippocampal arterioles to KCl, nitric oxide synthase inhibition with NG-nitro-L-arginine methyl ester and the nitric oxide donor sodium nitroprusside were investigated. Capillary density was quantified via immunohistochemistry. Cerebral blood flow increased during seizure vs. baseline in pregnant (118 ± 14 vs. 87 ± 9 mL/100 g/min; p < 0.05) and nonpregnant rats (106 ± 9 vs. 82 ± 9 mL/100 g/min; p < 0.05) but was unchanged in preeclamptic rats (79 ± 16 vs. 91 ± 4 mL/100 g/min; p > 0.05), suggesting impaired seizure-induced hyperemia in preeclampsia. Hippocampal arterioles from preeclamptic rats had less basal tone, and dilated less to 15 mM KCl (9 ± 8%) vs. pregnant (61 ± 27%) and nonpregnant rats (20 ± 11%). L-NAME had no effect on hippocampal arterioles in any group, but dilation to sodium nitroprusside was similar. Structurally, hippocampal arterioles from preeclamptic rats underwent inward hypotrophic remodeling and capillary rarefaction. Impaired seizure-induced hyperemia, vascular dysfunction, and limited vasodilatory reserve of hippocampal arterioles could potentiate hippocampal injury in preeclampsia especially during eclampsia.
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Affiliation(s)
- Abbie C Johnson
- 1 Department of Neurological Sciences, University of Vermont College of Medicine, Burlington, USA
| | - Marilyn J Cipolla
- 1 Department of Neurological Sciences, University of Vermont College of Medicine, Burlington, USA.,2 Department of Obstetrics, Gynecology, and Reproductive Sciences, University of Vermont College of Medicine, Burlington, USA.,3 Department of Pharmacology, University of Vermont College of Medicine, Burlington, USA
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31
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Hinman JD, Rost NS, Leung TW, Montaner J, Muir KW, Brown S, Arenillas JF, Feldmann E, Liebeskind DS. Principles of precision medicine in stroke. J Neurol Neurosurg Psychiatry 2017; 88:54-61. [PMID: 27919057 DOI: 10.1136/jnnp-2016-314587] [Citation(s) in RCA: 52] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/13/2016] [Revised: 09/30/2016] [Accepted: 10/03/2016] [Indexed: 01/22/2023]
Abstract
The era of precision medicine has arrived and conveys tremendous potential, particularly for stroke neurology. The diagnosis of stroke, its underlying aetiology, theranostic strategies, recurrence risk and path to recovery are populated by a series of highly individualised questions. Moreover, the phenotypic complexity of a clinical diagnosis of stroke makes a simple genetic risk assessment only partially informative on an individual basis. The guiding principles of precision medicine in stroke underscore the need to identify, value, organise and analyse the multitude of variables obtained from each individual to generate a precise approach to optimise cerebrovascular health. Existing data may be leveraged with novel technologies, informatics and practical clinical paradigms to apply these principles in stroke and realise the promise of precision medicine. Importantly, precision medicine in stroke will only be realised once efforts to collect, value and synthesise the wealth of data collected in clinical trials and routine care starts. Stroke theranostics, the ultimate vision of synchronising tailored therapeutic strategies based on specific diagnostic data, demand cerebrovascular expertise on big data approaches to clinically relevant paradigms. This review considers such challenges and delineates the principles on a roadmap for rational application of precision medicine to stroke and cerebrovascular health.
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Affiliation(s)
- Jason D Hinman
- Department of Neurology, Neurovascular Imaging Research Core and the UCLA Stroke Center, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
| | - Natalia S Rost
- Department of Neurology, Philip Kistler Stroke Research Center, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Thomas W Leung
- Division of Neurology, Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Shatin, Hong Kong
| | - Joan Montaner
- Neurovascular Research Laboratory, Vall d'Hebron Research Institute (VHIR), Barcelona & IBIS Stroke Programme, Hospital Virgen Macarena-Rocio, Sevilla, Spain
| | - Keith W Muir
- Institute of Neuroscience & Psychology, Glasgow, UK
| | - Scott Brown
- Altair Biostatistics, St. Louis Park, Minnesota, USA
| | - Juan F Arenillas
- Stroke Unit, Department of Neurology and Medicine, Hospital Clínico Universitario, Universidad de Valladolid, Valladolid, Spain
| | | | - David S Liebeskind
- Department of Neurology, Neurovascular Imaging Research Core and the UCLA Stroke Center, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
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32
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Hsu FC, Yuan M, Bowden DW, Xu J, Smith SC, Wagenknecht LE, Langefeld CD, Divers J, Register TC, Carr JJ, Williamson JD, Sink KM, Maldjian JA, Freedman BI. Adiposity is inversely associated with hippocampal volume in African Americans and European Americans with diabetes. J Diabetes Complications 2016; 30:1506-1512. [PMID: 27615667 PMCID: PMC5050135 DOI: 10.1016/j.jdiacomp.2016.08.012] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/05/2016] [Revised: 08/08/2016] [Accepted: 08/11/2016] [Indexed: 11/29/2022]
Abstract
AIMS To assess associations between body mass index (BMI), waist circumference (WC), and computed tomography-determined volumes of pericardial, visceral, and subcutaneous adipose tissue with magnetic resonance imaging-(MRI) based cerebral structure and cognitive performance in individuals with type 2 diabetes (T2D). METHODS This study was performed in 348 African Americans (AAs) and 256 European Americans (EAs) with T2D. Associations between adiposity measures with cerebral volumes of white matter (WMV), gray matter (GMV), white matter lesions, hippocampal GMV, and hippocampal WMV, cognitive performance and depression were examined using marginal models incorporating generalized estimating equations. All models were adjusted for age, sex, education, smoking, HbA1c, hypertension, statins, cardiovascular disease, MRI scanner (MRI outcomes only), and time between scans; some neuroimaging measures were additionally adjusted for intracranial volume. RESULTS Participants were 59.9% female with mean (SD) age 57.7(9.3)years, diabetes duration 9.6(6.8)years, and HbA1c 7.8(1.9)%. In AAs, inverse associations were detected between hippocampal GMV and both BMI (β [95% CI]-0.18 [-0.30, -0.07], P=0.0018) and WC (-0.23 [-0.35, -0.12], P=0.0001). In the full bi-ethnic sample, inverse associations were detected between hippocampal WMV and WC (P≤0.0001). Positive relationships were observed between BMI (P=0.0007) and WC (P<0.0001) with depression in EAs. CONCLUSIONS In patients with T2D, adiposity is inversely associated with hippocampal gray and white matter volumes.
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Affiliation(s)
- Fang-Chi Hsu
- Division of Public Health Sciences, Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, NC, USA; Center for Public Health Genomics, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Mingxia Yuan
- Department of Internal Medicine, Section on Nephrology, Wake Forest School of Medicine, Winston-Salem, NC, USA; Department of Endocrinology, Beijing Tongren Hospital, Capital Medical University, Beijing, China
| | - Donald W Bowden
- Centers for Genomics and Personalized Medicine Research & Diabetes Research, Wake Forest School of Medicine, Winston-Salem, NC, USA; Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Jianzhao Xu
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - S Carrie Smith
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Lynne E Wagenknecht
- Division of Public Health Sciences, Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, NC, USA; Center for Public Health Genomics, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Carl D Langefeld
- Division of Public Health Sciences, Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, NC, USA; Center for Public Health Genomics, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Jasmin Divers
- Division of Public Health Sciences, Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, NC, USA; Center for Public Health Genomics, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Thomas C Register
- Department of Pathology, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - J Jeffrey Carr
- Department of Radiology, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Jeff D Williamson
- Department of Internal Medicine, Section on Gerontology and Geriatric Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Kaycee M Sink
- Department of Internal Medicine, Section on Gerontology and Geriatric Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Joseph A Maldjian
- Department of Radiology, Advanced Neuroscience Imaging Research (ANSIR) Laboratory, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Barry I Freedman
- Center for Public Health Genomics, Wake Forest School of Medicine, Winston-Salem, NC, USA; Department of Internal Medicine, Section on Nephrology, Wake Forest School of Medicine, Winston-Salem, NC, USA.
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33
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van Uden IW, van der Holst HM, van Leijsen EM, Tuladhar AM, van Norden AG, de Laat KF, Claassen JA, van Dijk EJ, Kessels RP, Richard E, Tendolkar I, de Leeuw FE. Late-onset depressive symptoms increase the risk of dementia in small vessel disease. Neurology 2016; 87:1102-9. [DOI: 10.1212/wnl.0000000000003089] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2015] [Accepted: 05/30/2016] [Indexed: 11/15/2022] Open
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34
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Pasi M, van Uden IWM, Tuladhar AM, de Leeuw FE, Pantoni L. White Matter Microstructural Damage on Diffusion Tensor Imaging in Cerebral Small Vessel Disease: Clinical Consequences. Stroke 2016; 47:1679-84. [PMID: 27103015 DOI: 10.1161/strokeaha.115.012065] [Citation(s) in RCA: 59] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2015] [Accepted: 03/22/2016] [Indexed: 11/16/2022]
Affiliation(s)
- Marco Pasi
- From the NEUROFARBA Department, Neuroscience Section, University of Florence, Florence, Italy (M.P., L.P.); and Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands (I.W.M.v.U., A.M.T., F.-E.d.L.)
| | - Inge W M van Uden
- From the NEUROFARBA Department, Neuroscience Section, University of Florence, Florence, Italy (M.P., L.P.); and Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands (I.W.M.v.U., A.M.T., F.-E.d.L.)
| | - Anil M Tuladhar
- From the NEUROFARBA Department, Neuroscience Section, University of Florence, Florence, Italy (M.P., L.P.); and Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands (I.W.M.v.U., A.M.T., F.-E.d.L.)
| | - Frank-Erik de Leeuw
- From the NEUROFARBA Department, Neuroscience Section, University of Florence, Florence, Italy (M.P., L.P.); and Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands (I.W.M.v.U., A.M.T., F.-E.d.L.)
| | - Leonardo Pantoni
- From the NEUROFARBA Department, Neuroscience Section, University of Florence, Florence, Italy (M.P., L.P.); and Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands (I.W.M.v.U., A.M.T., F.-E.d.L.).
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35
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van Uden I, van der Holst H, Schaapsmeerders P, Tuladhar A, van Norden A, de Laat K, Norris D, Claassen J, van Dijk E, Richard E, Kessels R, de Leeuw FE. Baseline white matter microstructural integrity is not related to cognitive decline after 5 years: The RUN DMC study. BBA CLINICAL 2015; 4:108-114. [PMID: 26676146 PMCID: PMC4661735 DOI: 10.1016/j.bbacli.2015.10.001] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/10/2015] [Revised: 10/18/2015] [Accepted: 10/21/2015] [Indexed: 01/20/2023]
Affiliation(s)
- I.W.M. van Uden
- Radboudumc, Donders Institute for Brain, Cognition and Behaviour, Department of Neurology, The Netherlands
| | - H.M. van der Holst
- Radboudumc, Donders Institute for Brain, Cognition and Behaviour, Department of Neurology, The Netherlands
| | - P. Schaapsmeerders
- Radboudumc, Donders Institute for Brain, Cognition and Behaviour, Department of Neurology, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Department of Medical Psychology, Nijmegen, The Netherlands
| | - A.M. Tuladhar
- Radboudumc, Donders Institute for Brain, Cognition and Behaviour, Department of Neurology, The Netherlands
| | | | - K.F. de Laat
- HagaZiekenhuis Den Haag, Department of Neurology, The Netherlands
| | - D.G. Norris
- Radboud University Nijmegen, Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, The Netherlands
- Erwin L. Hahn Institute for Magnetic Resonance Imaging, University of Duisburg-Essen, Arendahls Wiese 199, Tor 3, D-45141 Essen, Germany
| | - J.A.H.R. Claassen
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Department of Geriatrics, Nijmegen, The Netherlands
| | - E.J. van Dijk
- Radboudumc, Donders Institute for Brain, Cognition and Behaviour, Department of Neurology, The Netherlands
| | - E. Richard
- Radboudumc, Donders Institute for Brain, Cognition and Behaviour, Department of Neurology, The Netherlands
| | - R.P.C. Kessels
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Department of Geriatrics, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Department of Medical Psychology, Nijmegen, The Netherlands
| | - F.-E. de Leeuw
- Radboudumc, Donders Institute for Brain, Cognition and Behaviour, Department of Neurology, The Netherlands
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