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Wang Y, Li Y, Jiao S, Pan Y, Deng X, Qin Y, Zhao D, Liu Z. Correlation analysis and predictive model construction of metabolic syndrome, complete blood count-derived inflammatory markers, and overall burden of cerebral small vessel disease. Heliyon 2024; 10:e35065. [PMID: 39220940 PMCID: PMC11365336 DOI: 10.1016/j.heliyon.2024.e35065] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2023] [Revised: 07/20/2024] [Accepted: 07/22/2024] [Indexed: 09/04/2024] Open
Abstract
Background The high burden of cerebral small vessel disease (CSVD) on neuroimaging is a significant risk factor for stroke, cognitive dysfunction, and emotional disorders. Currently, there is a lack of studies investigating the correlation between metabolic syndrome (MetS), complete blood count-derived inflammatory markers, and total CSVD burden. This study aims to evaluate the total CSVD imaging load using machine learning (ML) algorithms and to explore further the relationship between MetS, complete blood count-derived inflammatory markers, and CSVD load. Methods We included CSVD patients from Xijing Hospital (2012-2022). Univariate and lasso regression analyses identified variables linked to CSVD neuroimaging burden. Six ML models predicted CSVD burden based on MetS and inflammatory markers. Model performance was evaluated using ROCauc, PRauc, DCA, and calibration curves. The SHAP method validated model interpretability. The best-performing model was selected to develop a web-based calculator using the Shiny package. Results The Logistic regression model outperformed others in predicting CSVD burden. The model incorporated MetS, neutrophil-to-lymphocyte ratio (NLR), homocysteine (Hcy), age, smoking status, cystatin C (CysC), uric acid (UA), and prognostic nutritional index (PNI). Conclusion MetS, NLR, Hcy and CSVD high load were positively correlated, and the Logistic regression model could accurately predict the total CSVD load degree.
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Affiliation(s)
- Yang Wang
- Department of Neurology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
- Department of Neurology, Bethune International Peace Hospital, Shijiazhuang, China
| | - Yang Li
- Department of Neurology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Shusheng Jiao
- Department of Neurology, Bethune International Peace Hospital, Shijiazhuang, China
| | - Yuanhang Pan
- Department of Neurology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Xiwei Deng
- Department of Neurology, Bethune International Peace Hospital, Shijiazhuang, China
| | - Yunlong Qin
- Department of Neurology, Bethune International Peace Hospital, Shijiazhuang, China
| | - Di Zhao
- Department of Neurology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Zhirong Liu
- Department of Neurology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
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Pushpam M, Talukdar A, Anilkumar S, Maurya SK, Issac TG, Diwakar L. Recurrent endothelin-1 mediated vascular insult leads to cognitive impairment protected by trophic factor pleiotrophin. Exp Neurol 2024; 381:114938. [PMID: 39197707 DOI: 10.1016/j.expneurol.2024.114938] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2024] [Revised: 08/12/2024] [Accepted: 08/24/2024] [Indexed: 09/01/2024]
Abstract
Vascular dementia (VaD) is a complex neurodegenerative condition, with cerebral small vessel dysfunctions as the central role in its pathogenesis. Given the lack of suitable animal models to study the disease pathogenesis, we developed a mouse model to closely emulate the clinical scenarios of recurrent transient ischemic attacks (TIAs) leading to VaD using vasoconstricting peptide Endothelin-1(ET-1). We observed that administration of ET-1 led to blood-brain barrier (BBB) disruption and detrimental changes in its components, such as endothelial cells and pericytes, along with neuronal loss and synaptic dysfunction, resulting in irreversible memory loss. Further, in our pursuit of understanding potential interventions, we co-administered pleiotrophin (PTN) alongside ET-1 injections. PTN exhibited remarkable efficacy in preserving vital components of the BBB, including endothelial cells and pericytes, thereby restoring BBB integrity, preventing neuronal loss, and enhancing memory function. Our findings give a valuable framework for understanding the detrimental effects of multiple TIAs on brain health and provide a useful animal model to explore VaD's underlying mechanisms further and pave the way for promising therapies.
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Affiliation(s)
- Mayank Pushpam
- Centre for Brain Research, Indian Institute of Science, Bangalore 560012, India; Manipal Academy of Higher Education (MAHE), Manipal 576104, India
| | - Ankita Talukdar
- Centre for Brain Research, Indian Institute of Science, Bangalore 560012, India
| | - Shobha Anilkumar
- Centre for Brain Research, Indian Institute of Science, Bangalore 560012, India
| | | | - Thomas Gregor Issac
- Centre for Brain Research, Indian Institute of Science, Bangalore 560012, India
| | - Latha Diwakar
- Centre for Brain Research, Indian Institute of Science, Bangalore 560012, India.
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Hosoya M, Toi S, Yoshizawa H, Kitagawa K. Slow Gait Speed Predicts Incident Dementia, Mortality, and Long-Term Functional Outcome in Cerebral Small-Vessel Disease. J Alzheimers Dis 2024:JAD240304. [PMID: 39213068 DOI: 10.3233/jad-240304] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/04/2024]
Abstract
Background Gait impairment is observed in patients with small vessel disease (SVD); however, the association between gait function and long-term outcome remains unclear. Objectives This study aimed to clarify the predictive value of gait function on incident dementia, survival and functional outcome. Methods Data were derived from a Japanese cohort of patients with SVD. This study included 522 participants who underwent 3-m timed up and go test (TUG), and gait speed, TUG time, was divided into tertiles. Magnetic resonance imaging was used to evaluate severity of white matter hyperintensities, lacunes, and medial temporal atrophy. Primary outcome was dementia. All-cause death and functional outcome by modified Rankin scale at the last visit was also evaluated. Results The median age was 71 years, and median TUG time was 9.91 s. During follow-up period of 4.8 years, 32 cases of dementia occurred. Cox proportional hazard analysis revealed that slow gait speed (TUG time > 10.88 s) was associated with a significantly higher risk of incident dementia than fast (TUG time < 9.03) and middle (TUG time, 9.04-10.87 s) speeds after adjusting risk factors, Mini-Mental State Examination, SVD severity and brain atrophy (adjusted hazard ratio, 2.73; 95% confidence interval, 1.16-6.42, p = 0.022). Slow speed was also associated with mortality and poor functional outcome compared with other speeds (adjusted odds ratio, 4.19; 95% confidence interval 1.92-9.18, p < 0.001). Conclusions Gait function was associated with incident dementia, mortality and poor functional outcome independently of cognitive function, brain atrophy, and SVD severity.
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Affiliation(s)
- Megumi Hosoya
- Department of Neurology, Tokyo Women's Medical University Hospital, Tokyo, Japan
| | - Sono Toi
- Department of Neurology, Tokyo Women's Medical University Hospital, Tokyo, Japan
- Department of Medicine, Tokyo Women's Medical University, Adachi Medical Center, Tokyo, Japan
| | - Hiroshi Yoshizawa
- Department of Neurology, Tokyo Women's Medical University Hospital, Tokyo, Japan
- Department of Neurology, Tokyo Women's Medical University, Yachiyo Medical Center, Yachiyo, Japan
| | - Kazuo Kitagawa
- Department of Neurology, Tokyo Women's Medical University Hospital, Tokyo, Japan
- Department of Neurology, Suita Municipal Hospital, Suita, Osaka, Japan
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Mogi M. Small vessels cause big problems. Hypertens Res 2024:10.1038/s41440-024-01811-7. [PMID: 39138366 DOI: 10.1038/s41440-024-01811-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2024] [Accepted: 07/01/2024] [Indexed: 08/15/2024]
Affiliation(s)
- Masaki Mogi
- Department of Pharmacology, Ehime University, Graduate School of Medicine, Shitsukawa, Tohon, Ehime, 791-0295, Japan.
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Li N, Gao Y, Li LT, Hu YD, Ling L, Jia N, Chen YJ, Meng YN, Jiang Y. Development and validation of a nomogram predictive model for cognitive impairment in cerebral small vessel disease: a comprehensive retrospective analysis. Front Neurol 2024; 15:1373306. [PMID: 38952470 PMCID: PMC11215066 DOI: 10.3389/fneur.2024.1373306] [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: 01/25/2024] [Accepted: 06/06/2024] [Indexed: 07/03/2024] Open
Abstract
Background Cerebral small vessel disease (CSVD) is a common neurodegenerative condition in the elderly, closely associated with cognitive impairment. Early identification of individuals with CSVD who are at a higher risk of developing cognitive impairment is crucial for timely intervention and improving patient outcomes. Objective The aim of this study is to construct a predictive model utilizing LASSO regression and binary logistic regression, with the objective of precisely forecasting the risk of cognitive impairment in patients with CSVD. Methods The study utilized LASSO regression for feature selection and logistic regression for model construction in a cohort of CSVD patients. The model's validity was assessed through calibration curves and decision curve analysis (DCA). Results A nomogram was developed to predict cognitive impairment, incorporating hypertension, CSVD burden, apolipoprotein A1 (ApoA1) levels, and age. The model exhibited high accuracy with AUC values of 0.866 and 0.852 for the training and validation sets, respectively. Calibration curves confirmed the model's reliability, and DCA highlighted its clinical utility. The model's sensitivity and specificity were 75.3 and 79.7% for the training set, and 76.9 and 74.0% for the validation set. Conclusion This study successfully demonstrates the application of machine learning in developing a reliable predictive model for cognitive impairment in CSVD. The model's high accuracy and robust predictive capability provide a crucial tool for the early detection and intervention of cognitive impairment in patients with CSVD, potentially improving outcomes for this specific condition.
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Affiliation(s)
- Ning Li
- Department of Neurology, Affiliated Hospital of Hebei University, Baoding, China
| | - Yan Gao
- Department of Neurology, Renmin Hospital of Wuhan University, Wuhan, China
| | - Li-tao Li
- Department of Neurology, Hebei General Hospital, Shijiazhuang, China
| | - Ya-dong Hu
- Department of Neurology, Affiliated Hospital of Hebei University, Baoding, China
| | - Li Ling
- Department of Neurology, Affiliated Hospital of Hebei University, Baoding, China
| | - Nan Jia
- Department of Neurology, Affiliated Hospital of Hebei University, Baoding, China
| | - Ya-jing Chen
- Department of Neurology, Affiliated Hospital of Hebei University, Baoding, China
| | - Ya-nan Meng
- Department of Neurology, Affiliated Hospital of Hebei University, Baoding, China
| | - Ye Jiang
- Department of Neurology, Affiliated Hospital of Hebei University, Baoding, China
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Yang J, Xiao R, Liu Y, He C, Han L, Xu X, Chen M, Zhong J. Spatiotemporal consistency analysis of cerebral small vessel disease: an rs-fMRI study. Front Neurosci 2024; 18:1385960. [PMID: 38841094 PMCID: PMC11150806 DOI: 10.3389/fnins.2024.1385960] [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: 02/14/2024] [Accepted: 05/08/2024] [Indexed: 06/07/2024] Open
Abstract
Introduction Cerebral small vessel disease (SVD) affects older adults, but traditional approaches have limited the understanding of the neural mechanisms of SVD. This study aimed to explore the effects of SVD on brain regions and its association with cognitive decline using the four-dimensional (spatiotemporal) consistency of local neural activity (FOCA) method. Methods Magnetic resonance imaging data from 42 patients with SVD and 38 healthy controls (HCs) were analyzed using the FOCA values. A two-sample t test was performed to compare the differences in FOCA values in the brain between the HCs and SVD groups. Pearson correlation analysis was conducted to analyze the association of various brain regions with SVD scores. Results The results revealed that the FOCA values in the right frontal_inf_oper, right temporal_pole_sup, and default mode network decreased, whereas those in the temporal_inf, hippocampus, basal ganglia, and cerebellum increased, in patients with SVD. Most of these varying brain regions were negatively correlated with SVD scores. Discussion This study suggested that the FOCA approach might have the potential to provide useful insights into the understanding of the neurophysiologic mechanisms of patients with SVD.
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Affiliation(s)
- Jie Yang
- Department of Radiology, Zigong First People’s Hospital, Zigong, China
| | - Rui Xiao
- Department of Radiology, Zigong First People’s Hospital, Zigong, China
| | - Yujian Liu
- Department of Radiology, Zigong First People’s Hospital, Zigong, China
- Sichuan Vocational College of Health and Rehabilitation, Zigong, China
| | - Chaoliang He
- Department of Radiology, Zigong First People’s Hospital, Zigong, China
| | - Limei Han
- Department of Radiology, Zigong First People’s Hospital, Zigong, China
- North Sichuan Medical College, Nanchong, China
| | - Xiaoya Xu
- Department of Neurology, Zigong First People’s Hospital, Zigong, China
| | - Meining Chen
- MR Research and Collaboration, Siemens Healthineers, Shanghai, China
| | - Jianquan Zhong
- Department of Radiology, Zigong First People’s Hospital, Zigong, China
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Marcolini S, Mondragón JD, Bron EE, Biessels GJ, Claassen JA, Papma JM, Middelkoop H, Dierckx RA, Borra RJ, Ramakers IH, van der Flier WM, Maurits NM, De Deyn PP. Small vessel disease burden and functional brain connectivity in mild cognitive impairment. CEREBRAL CIRCULATION - COGNITION AND BEHAVIOR 2023; 6:100192. [PMID: 38174052 PMCID: PMC10758699 DOI: 10.1016/j.cccb.2023.100192] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/11/2023] [Revised: 11/15/2023] [Accepted: 11/27/2023] [Indexed: 01/05/2024]
Abstract
Background The role of small vessel disease in the development of dementia is not yet completely understood. Functional brain connectivity has been shown to differ between individuals with and without cerebral small vessel disease. However, a comprehensive measure of small vessel disease quantifying the overall damage on the brain is not consistently used and studies using such measure in mild cognitive impairment individuals are missing. Method Functional brain connectivity differences were analyzed between mild cognitive impairment individuals with absent or low (n = 34) and high (n = 34) small vessel disease burden using data from the Parelsnoer Institute, a Dutch multicenter study. Small vessel disease was characterized using an ordinal scale considering: lacunes, microbleeds, perivascular spaces in the basal ganglia, and white matter hyperintensities. Resting state functional MRI data using 3 Tesla scanners was analyzed with group-independent component analysis using the CONN toolbox. Results Functional connectivity between areas of the cerebellum and between the cerebellum and the thalamus and caudate nucleus was higher in the absent or low small vessel disease group compared to the high small vessel disease group. Conclusion These findings might suggest that functional connectivity of mild cognitive impairment individuals with low or absent small vessel disease burden is more intact than in mild cognitive impairment individuals with high small vessel disease. These brain areas are mainly responsible for motor, attentional and executive functions, domains which in previous studies were found to be mostly associated with small vessel disease markers. Our results support findings on the involvement of the cerebellum in cognitive functioning.
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Affiliation(s)
- Sofia Marcolini
- Department of Neurology, University Medical Center Groningen, University of Groningen, Groningen 9713 GZ, the Netherlands
| | - Jaime D. Mondragón
- Department of Neurology, University Medical Center Groningen, University of Groningen, Groningen 9713 GZ, the Netherlands
- Universidad Nacional Autónoma de México, Instituto de Neurobiología, Departamento de Neurobiología Conductual y Cognitiva, Laboratorio de Psicofisiología, Querétaro 76230, Mexico
- San Diego State University, Department of Psychology, Life-Span Human Senses Lab, San Diego, California 92182, USA
| | - Esther E. Bron
- Department of Radiology & Nuclear Medicine, Erasmus MC, Rotterdam 3015 GD, the Netherlands
| | - Geert J. Biessels
- Department of Neurology, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht 3584 CX, the Netherlands
| | - Jurgen A.H.R. Claassen
- Department of Geriatrics, Radboud University Medical Center and Donders Institute, Nijmegen 6525 GD, the Netherlands
- Department of Cardiovascular Sciences, University of Leicester, Leicester LE1 7RH, United Kingdom
| | - Janne M. Papma
- Department of Radiology & Nuclear Medicine, Erasmus MC, Rotterdam 3015 GD, the Netherlands
- Department of Neurology and Alzheimer Center Erasmus MC, Erasmus MC University Medical Center, Rotterdam 3015 GD, the Netherlands
| | - Huub Middelkoop
- Institute of Psychology, Health, Medical and Neuropsychology Unit, Leiden University, Leiden 2316 XC, the Netherlands
- Department of Neurology, Leiden University Medical Centre, Leiden 2333 ZA, the Netherlands
| | - Rudi A.J.O. Dierckx
- Department of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, Groningen 9713 GZ, the Netherlands
| | - Ronald J.H. Borra
- Department of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, Groningen 9713 GZ, the Netherlands
| | - Inez H.G.B. Ramakers
- Alzheimer Center Limburg, School for Mental Health and Neuroscience, Maastricht University, Maastricht 6229 ER, the Netherlands
| | - Wiesje M. van der Flier
- Department of Neurology, Alzheimer Center Amsterdam, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam 1081 HZ, the Netherlands
- Department of Epidemiology & Data Sciences, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam 1117, the Netherlands
| | - Natasha M. Maurits
- Department of Neurology, University Medical Center Groningen, University of Groningen, Groningen 9713 GZ, the Netherlands
| | - Peter P. De Deyn
- Department of Neurology, University Medical Center Groningen, University of Groningen, Groningen 9713 GZ, the Netherlands
- Laboratory of Neurochemistry and Behavior, University of Antwerp, Antwerp 2610, Belgium
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