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Kieliszek M, Sapazhenkava K. The Promising Role of Selenium and Yeast in the Fight Against Protein Amyloidosis. Biol Trace Elem Res 2024:10.1007/s12011-024-04245-x. [PMID: 38829477 DOI: 10.1007/s12011-024-04245-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/16/2024] [Accepted: 05/20/2024] [Indexed: 06/05/2024]
Abstract
In recent years, increasing attention has been paid to research on diseases related to the deposition of misfolded proteins (amyloids) in various organs. Moreover, modern scientists emphasise the importance of selenium as a bioelement necessary for the proper functioning of living organisms. The inorganic form of selenium-sodium selenite (redox-active)-can prevent the formation of an insoluble polymer in proteins. It is very important to undertake tasks aimed at understanding the mechanisms of action of this element in inhibiting the formation of various types of amyloid. Furthermore, yeast cells play an important role in this matter as a eukaryotic model organism, which is intensively used in molecular research on protein amyloidosis. Due to the lack of appropriate treatment in the general population, the problem of amyloidosis remains unsolved. This extracellular accumulation of amyloid is one of the main factors responsible for the occurrence of Alzheimer's disease. The review presented here contains scientific information discussing a brief description of the possibility of amyloid formation in cells and the use of selenium as a factor preventing the formation of these protein aggregates. Recent studies have shown that the yeast model can be successfully used as a eukaryotic organism in biotechnological research aimed at understanding the essence of the entire amyloidosis process. Understanding the mechanisms that regulate the reaction of yeast to selenium and the phenomenon of amyloidosis is important in the aetiology and pathogenesis of various disease states. Therefore, it is imperative to conduct further research and analysis aimed at explaining and confirming the role of selenium in the processes of protein misfolding disorders. The rest of the article discusses the characteristics of food protein amyloidosis and their use in the food industry. During such tests, their toxicity is checked because not all food proteins can produce amyloid that is toxic to cells. It should also be noted that a moderate diet is beneficial for the corresponding disease relief caused by amyloidosis.
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Affiliation(s)
- Marek Kieliszek
- Department of Food Biotechnology and Microbiology, Institute of Food Sciences, Warsaw University of Life Sciences-SGGW, Nowoursynowska 159 C, Warsaw, 02-776, Poland.
| | - Katsiaryna Sapazhenkava
- Department of Food Biotechnology and Microbiology, Institute of Food Sciences, Warsaw University of Life Sciences-SGGW, Nowoursynowska 159 C, Warsaw, 02-776, Poland
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Liu L, Gracely EJ, Zhao X, Gliebus GP, May NS, Volpe SL, Shi J, DiMaria-Ghalili RA, Eisen HJ. Association of multiple metabolic and cardiovascular markers with the risk of cognitive decline and mortality in adults with Alzheimer's disease and AD-related dementia or cognitive decline: a prospective cohort study. Front Aging Neurosci 2024; 16:1361772. [PMID: 38628973 PMCID: PMC11020085 DOI: 10.3389/fnagi.2024.1361772] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2023] [Accepted: 02/26/2024] [Indexed: 04/19/2024] Open
Abstract
Background and objectives There is a scarcity of data stemming from large-scale epidemiological longitudinal studies focusing on potentially preventable and controllable risk factors for Alzheimer's disease (AD) and AD-related dementia (ADRD). This study aimed to examine the effect of multiple metabolic factors and cardiovascular disorders on the risk of cognitive decline and AD/ADRD. Methods We analyzed a cohort of 6,440 participants aged 45-84 years at baseline. Multiple metabolic and cardiovascular disorder factors included the five components of the metabolic syndrome [waist circumference, high blood pressure (HBP), elevated glucose and triglyceride (TG) concentrations, and reduced high-density lipoprotein cholesterol (HDL-C) concentrations], C-reactive protein (CRP), fibrinogen, interleukin-6 (IL-6), factor VIII, D-dimer, and homocysteine concentrations, carotid intimal-medial thickness (CIMT), and urine albumin-to-creatinine ratio (ACR). Cognitive decline was defined using the Cognitive Abilities Screening Instrument (CASI) score, and AD/ADRD cases were classified using clinical diagnoses. Results Over an average follow-up period of 13 years, HBP and elevated glucose, CRP, homocysteine, IL-6, and ACR concentrations were significantly associated with the risk of mortality in the individuals with incident AD/ADRD or cognitive decline. Elevated D-dimer and homocysteine concentrations, as well as elevated ACR were significantly associated with incident AD/ADRD. Elevated homocysteine and ACR were significantly associated with cognitive decline. A dose-response association was observed, indicating that an increased number of exposures to multiple risk factors corresponded to a higher risk of mortality in individuals with cognitive decline or with AD/ADRD. Conclusion Findings from our study reaffirm the significance of preventable and controllable factors, including HBP, hyperglycemia, elevated CRP, D-dimer, and homocysteine concentrations, as well as, ACR, as potential risk factors for cognitive decline and AD/ADRD.
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Affiliation(s)
- Longjian Liu
- Department of Epidemiology and Biostatistics, Dornsife School of Public Health, Drexel University, Philadelphia, PA, United States
| | - Edward J. Gracely
- Department of Epidemiology and Biostatistics, Dornsife School of Public Health, Drexel University, Philadelphia, PA, United States
- Department of Family, Community & Preventive Medicine, College of Medicine, Drexel University, Philadelphia, PA, United States
| | - Xiaopeng Zhao
- Department of Mechanical, Aerospace, and Biomedical Engineering, University of Tennessee, Knoxville, Knoxville, TN, United States
| | - Gediminas P. Gliebus
- Department of Neurology, College of Medicine, Drexel University Philadelphia, Philadelphia, PA, United States
| | - Nathalie S. May
- Department of Medicine, College of Medicine, Drexel University, Philadelphia, PA, United States
| | - Stella L. Volpe
- Department of Human Nutrition, Foods, and Exercise, Virginia Polytechnic Institute and State University, Blacksburg, VA, United States
| | - Jingyi Shi
- Department of Mathematics and Statistics, Mississippi State University, Starkville, MS, United States
| | - Rose Ann DiMaria-Ghalili
- Doctoral Nursing Department, Nutrition Science Department, College of Nursing and Health Professions, Drexel University, Philadelphia, PA, United States
| | - Howard J. Eisen
- Clinical Research for the Advanced Cardiac and Pulmonary Vascular Disease Program, Thomas Jefferson University Hospital, Philadelphia, PA, United States
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Chen A, Li Q, Huang Y, Li Y, Chuang YN, Hu X, Guo S, Wu Y, Guo Y, Bian J. Feasibility of Identifying Factors Related to Alzheimer's Disease and Related Dementia in Real-World Data. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.02.10.24302621. [PMID: 38405723 PMCID: PMC10889002 DOI: 10.1101/2024.02.10.24302621] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/27/2024]
Abstract
A comprehensive view of factors associated with AD/ADRD will significantly aid in studies to develop new treatments for AD/ADRD and identify high-risk populations and patients for prevention efforts. In our study, we summarized the risk factors for AD/ADRD by reviewing existing meta-analyses and review articles on risk and preventive factors for AD/ADRD. In total, we extracted 477 risk factors in 10 categories from 537 studies. We constructed an interactive knowledge map to disseminate our study results. Most of the risk factors are accessible from structured Electronic Health Records (EHRs), and clinical narratives show promise as information sources. However, evaluating genomic risk factors using RWD remains a challenge, as genetic testing for AD/ADRD is still not a common practice and is poorly documented in both structured and unstructured EHRs. Considering the constantly evolving research on AD/ADRD risk factors, literature mining via NLP methods offers a solution to automatically update our knowledge map.
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Affiliation(s)
- Aokun Chen
- Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, 1889 Museum Rd, Suite 7000, Gainesville, FL 32610
| | - Qian Li
- Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, 1889 Museum Rd, Suite 7000, Gainesville, FL 32610
| | - Yu Huang
- Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, 1889 Museum Rd, Suite 7000, Gainesville, FL 32610
| | - Yongqiu Li
- Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, 1889 Museum Rd, Suite 7000, Gainesville, FL 32610
| | - Yu-Neng Chuang
- Department of Computer Science, George R. Brown School of Engineering, Rice University, 6100 Main St., Houston, TX 77005
| | - Xia Hu
- Department of Computer Science, George R. Brown School of Engineering, Rice University, 6100 Main St., Houston, TX 77005
| | - Serena Guo
- Department of Pharmaceutical Outcomes & Policy, College of Pharmacy, University of Florida, 1225 Center Drive, Gainesville, FL 32610
| | - Yonghui Wu
- Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, 1889 Museum Rd, Suite 7000, Gainesville, FL 32610
| | - Yi Guo
- Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, 1889 Museum Rd, Suite 7000, Gainesville, FL 32610
| | - Jiang Bian
- Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, 1889 Museum Rd, Suite 7000, Gainesville, FL 32610
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Wu A, Sharrett AR, Folsom AR, Alonso A, Walker KA, Gottesman RF, Gross AL, Rawlings AM, Schneider ALC, Coresh J. Midlife Hemostasis Measures, 20-Year Cognitive Decline, and Incident Dementia. Neurology 2023; 101:e1697-e1707. [PMID: 37652701 PMCID: PMC10624500 DOI: 10.1212/wnl.0000000000207771] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2022] [Accepted: 06/27/2023] [Indexed: 09/02/2023] Open
Abstract
BACKGROUND AND OBJECTIVES Blood concentrations of hemostatic factors affect thrombosis and bleeding diathesis and may contribute to cognitive impairment through modifiable vascular pathologies. Whether hemostasis, assessed in middle age, is associated with late-life cognitive impairment remains largely unknown in a community-dwelling population. METHODS Using data from 14,128 participants with cognitive function measurements in 1990-1992 from the Atherosclerosis Risk in Communities study, we assessed the associations of hemostasis measures with 20-year changes in cognitive performance and incident dementia. Activated partial thromboplastin time (aPTT) and level of fibrinogen, von Willebrand factor (VWF), factor VIII, factor VII, factor XI, d-dimer, and soluble thrombomodulin were measured in 1987-1989 or 1993-1995. Hemostasis measures were categorized into quintiles, with the lowest quintile indicating low coagulability. Cognitive performance was characterized using a combined z-score from 3 tests (that is, delayed word recall test [DWRT], digit symbol substitution [DSST], and word fluency test [WFT]), assessed in 1990-1992, 1996-1998, and 2011-2013. Dementia was determined either from in-person evaluations or using dementia surveillance through 2017. Mixed-effects models and Cox proportional hazards models were used to assess cognitive trajectories and risk of dementia, respectively. RESULTS Among 12,765 participants with hemostasis measures in 1987-1989, who were aged 47-70 years at the first cognitive assessment, we observed significant trends of shorter aPTT (p for trend <0.001; difference in 20-year cognitive decline for fifth vs first quintile [Q5 vs Q1]: -0.104 [95% CI -0.160 to -0.048]) and higher levels of factor VII (p < 0.002; Q5 vs Q1: -0.085 [-0.142, -0.028]) and factor VIII (p = 0.033; Q4 vs Q1: -0.055 [-0.111, -0.000]) with greater 20-year cognitive declines. The associations with the decline in DSST were stronger than those with the decline in WFT or DWRT. Consistently, shorter aPTT and higher factor VIII levels were associated with higher dementia risk with HRs for Q5 vs Q1 of 1.23 (95% CI 1.07 to 1.42) and 1.17 (1.01-1.36), respectively, and p for trend of 0.008 and 0.024, respectively. DISCUSSION Overall, our study found consistent trend associations of aPTT and factor VIII measured in midlife with cognitive decline and incident dementia over 20 years, likely driven by vascular pathologies.
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Affiliation(s)
- Aozhou Wu
- From the Johns Hopkins University (A.W., A.R.S., A.L.G., J.C.), Bloomberg School of Public Health, Baltimore, MD; University of Minnesota (A.R.F.), School of Public Health, Minneapolis; Department of Epidemiology (A.A.), Rollins School of Public Health, Emory University, Atlanta, GA; Laboratory of Behavioral Neuroscience (K.A.W.), Intramural Research Program, National Institute on Aging, Baltimore; National Institute of Neurological Disorders and Stroke Intramural Program (R.F.G.), NIH, Bethesda, MD; Sanofi (A.M.R.), Cambridge, MA; and Division of Neurocritical Care (A.L.C.S.), Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia
| | - A Richey Sharrett
- From the Johns Hopkins University (A.W., A.R.S., A.L.G., J.C.), Bloomberg School of Public Health, Baltimore, MD; University of Minnesota (A.R.F.), School of Public Health, Minneapolis; Department of Epidemiology (A.A.), Rollins School of Public Health, Emory University, Atlanta, GA; Laboratory of Behavioral Neuroscience (K.A.W.), Intramural Research Program, National Institute on Aging, Baltimore; National Institute of Neurological Disorders and Stroke Intramural Program (R.F.G.), NIH, Bethesda, MD; Sanofi (A.M.R.), Cambridge, MA; and Division of Neurocritical Care (A.L.C.S.), Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia
| | - Aaron R Folsom
- From the Johns Hopkins University (A.W., A.R.S., A.L.G., J.C.), Bloomberg School of Public Health, Baltimore, MD; University of Minnesota (A.R.F.), School of Public Health, Minneapolis; Department of Epidemiology (A.A.), Rollins School of Public Health, Emory University, Atlanta, GA; Laboratory of Behavioral Neuroscience (K.A.W.), Intramural Research Program, National Institute on Aging, Baltimore; National Institute of Neurological Disorders and Stroke Intramural Program (R.F.G.), NIH, Bethesda, MD; Sanofi (A.M.R.), Cambridge, MA; and Division of Neurocritical Care (A.L.C.S.), Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia
| | - Alvaro Alonso
- From the Johns Hopkins University (A.W., A.R.S., A.L.G., J.C.), Bloomberg School of Public Health, Baltimore, MD; University of Minnesota (A.R.F.), School of Public Health, Minneapolis; Department of Epidemiology (A.A.), Rollins School of Public Health, Emory University, Atlanta, GA; Laboratory of Behavioral Neuroscience (K.A.W.), Intramural Research Program, National Institute on Aging, Baltimore; National Institute of Neurological Disorders and Stroke Intramural Program (R.F.G.), NIH, Bethesda, MD; Sanofi (A.M.R.), Cambridge, MA; and Division of Neurocritical Care (A.L.C.S.), Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia
| | - Keenan A Walker
- From the Johns Hopkins University (A.W., A.R.S., A.L.G., J.C.), Bloomberg School of Public Health, Baltimore, MD; University of Minnesota (A.R.F.), School of Public Health, Minneapolis; Department of Epidemiology (A.A.), Rollins School of Public Health, Emory University, Atlanta, GA; Laboratory of Behavioral Neuroscience (K.A.W.), Intramural Research Program, National Institute on Aging, Baltimore; National Institute of Neurological Disorders and Stroke Intramural Program (R.F.G.), NIH, Bethesda, MD; Sanofi (A.M.R.), Cambridge, MA; and Division of Neurocritical Care (A.L.C.S.), Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia
| | - Rebecca F Gottesman
- From the Johns Hopkins University (A.W., A.R.S., A.L.G., J.C.), Bloomberg School of Public Health, Baltimore, MD; University of Minnesota (A.R.F.), School of Public Health, Minneapolis; Department of Epidemiology (A.A.), Rollins School of Public Health, Emory University, Atlanta, GA; Laboratory of Behavioral Neuroscience (K.A.W.), Intramural Research Program, National Institute on Aging, Baltimore; National Institute of Neurological Disorders and Stroke Intramural Program (R.F.G.), NIH, Bethesda, MD; Sanofi (A.M.R.), Cambridge, MA; and Division of Neurocritical Care (A.L.C.S.), Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia
| | - Alden L Gross
- From the Johns Hopkins University (A.W., A.R.S., A.L.G., J.C.), Bloomberg School of Public Health, Baltimore, MD; University of Minnesota (A.R.F.), School of Public Health, Minneapolis; Department of Epidemiology (A.A.), Rollins School of Public Health, Emory University, Atlanta, GA; Laboratory of Behavioral Neuroscience (K.A.W.), Intramural Research Program, National Institute on Aging, Baltimore; National Institute of Neurological Disorders and Stroke Intramural Program (R.F.G.), NIH, Bethesda, MD; Sanofi (A.M.R.), Cambridge, MA; and Division of Neurocritical Care (A.L.C.S.), Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia
| | - Andreea M Rawlings
- From the Johns Hopkins University (A.W., A.R.S., A.L.G., J.C.), Bloomberg School of Public Health, Baltimore, MD; University of Minnesota (A.R.F.), School of Public Health, Minneapolis; Department of Epidemiology (A.A.), Rollins School of Public Health, Emory University, Atlanta, GA; Laboratory of Behavioral Neuroscience (K.A.W.), Intramural Research Program, National Institute on Aging, Baltimore; National Institute of Neurological Disorders and Stroke Intramural Program (R.F.G.), NIH, Bethesda, MD; Sanofi (A.M.R.), Cambridge, MA; and Division of Neurocritical Care (A.L.C.S.), Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia
| | - Andrea Lauren Christman Schneider
- From the Johns Hopkins University (A.W., A.R.S., A.L.G., J.C.), Bloomberg School of Public Health, Baltimore, MD; University of Minnesota (A.R.F.), School of Public Health, Minneapolis; Department of Epidemiology (A.A.), Rollins School of Public Health, Emory University, Atlanta, GA; Laboratory of Behavioral Neuroscience (K.A.W.), Intramural Research Program, National Institute on Aging, Baltimore; National Institute of Neurological Disorders and Stroke Intramural Program (R.F.G.), NIH, Bethesda, MD; Sanofi (A.M.R.), Cambridge, MA; and Division of Neurocritical Care (A.L.C.S.), Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia
| | - Josef Coresh
- From the Johns Hopkins University (A.W., A.R.S., A.L.G., J.C.), Bloomberg School of Public Health, Baltimore, MD; University of Minnesota (A.R.F.), School of Public Health, Minneapolis; Department of Epidemiology (A.A.), Rollins School of Public Health, Emory University, Atlanta, GA; Laboratory of Behavioral Neuroscience (K.A.W.), Intramural Research Program, National Institute on Aging, Baltimore; National Institute of Neurological Disorders and Stroke Intramural Program (R.F.G.), NIH, Bethesda, MD; Sanofi (A.M.R.), Cambridge, MA; and Division of Neurocritical Care (A.L.C.S.), Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia.
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Rana T, Jiang C, Banerjee S, Yi N, Zmijewski JW, Liu G, Liu RM. PAI-1 Regulation of p53 Expression and Senescence in Type II Alveolar Epithelial Cells. Cells 2023; 12:2008. [PMID: 37566086 PMCID: PMC10417428 DOI: 10.3390/cells12152008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Revised: 07/17/2023] [Accepted: 08/01/2023] [Indexed: 08/12/2023] Open
Abstract
Cellular senescence contributes importantly to aging and aging-related diseases, including idiopathic pulmonary fibrosis (IPF). Alveolar epithelial type II (ATII) cells are progenitors of alveolar epithelium, and ATII cell senescence is evident in IPF. Previous studies from this lab have shown that increased expression of plasminogen activator inhibitor 1 (PAI-1), a serine protease inhibitor, promotes ATII cell senescence through inducing p53, a master cell cycle repressor, and activating p53-p21-pRb cell cycle repression pathway. In this study, we further show that PAI-1 binds to proteasome components and inhibits proteasome activity and p53 degradation in human lung epithelial A549 cells and primary mouse ATII cells. This is associated with a senescence phenotype of these cells, manifested as increased p53 and p21 expression, decreased phosphorylated retinoblastoma protein (pRb), and increased senescence-associated beta-galactose (SA-β-gal) activity. Moreover, we find that, although overexpression of wild-type PAI-1 (wtPAI-1) or a secretion-deficient, mature form of PAI-1 (sdPAI-1) alone induces ATII cell senescence (increases SA-β-gal activity), only wtPAI-1 induces p53, suggesting that the premature form of PAI-1 is required for the interaction with the proteasome. In summary, our data indicate that PAI-1 can bind to proteasome components and thus inhibit proteasome activity and p53 degradation in ATII cells. As p53 is a master cell cycle repressor and PAI-1 expression is increased in many senescent cells, the results from this study will have a significant impact not only on ATII cell senescence/lung fibrosis but also on the senescence of other types of cells in different diseases.
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Affiliation(s)
- Tapasi Rana
- Division of Pulmonary, Allergy, and Critical Care, Department of Medicine, University of Alabama at Birmingham, Birmingham, AL 35294, USA
| | - Chunsun Jiang
- Division of Pulmonary, Allergy, and Critical Care, Department of Medicine, University of Alabama at Birmingham, Birmingham, AL 35294, USA
| | - Sami Banerjee
- Division of Pulmonary, Allergy, and Critical Care, Department of Medicine, University of Alabama at Birmingham, Birmingham, AL 35294, USA
| | - Nengjun Yi
- Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL 35294, USA
| | - Jaroslaw W. Zmijewski
- Division of Pulmonary, Allergy, and Critical Care, Department of Medicine, University of Alabama at Birmingham, Birmingham, AL 35294, USA
| | - Gang Liu
- Division of Pulmonary, Allergy, and Critical Care, Department of Medicine, University of Alabama at Birmingham, Birmingham, AL 35294, USA
| | - Rui-Ming Liu
- Division of Pulmonary, Allergy, and Critical Care, Department of Medicine, University of Alabama at Birmingham, Birmingham, AL 35294, USA
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Qin W, Li F, Jia L, Wang Q, Li Y, Wei Y, Li Y, Jin H, Jia J. Phosphorylated Tau 181 Serum Levels Predict Alzheimer’s Disease in the Preclinical Stage. Front Aging Neurosci 2022; 14:900773. [PMID: 35769604 PMCID: PMC9234327 DOI: 10.3389/fnagi.2022.900773] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Accepted: 05/10/2022] [Indexed: 11/17/2022] Open
Abstract
Background There is an urgent need for cost-effective, easy-to-measure biomarkers to identify subjects who will develop Alzheimer’s disease (AD), especially at the pre-symptomatic stage. This stage can be determined in autosomal dominant AD (ADAD) which offers the opportunity to observe the dynamic biomarker changes during the life-course of AD stages. This study aimed to investigate serum biomarkers during different AD stages and potential novel protein biomarkers of presymptomatic AD. Methods In the first stage, 32 individuals [20 mutation carriers including 10 with AD, and 10 with mild cognitive impairment (MCI), and 12 healthy controls] from ADAD families were analyzed. All subjects underwent a complete clinical evaluation and a comprehensive neuropsychological battery. Serum samples were collected from all subjects, and antibody arrays were used to analyze 170 proteins in these samples. The most promising biomarkers were identified during this screening and were then measured in serum samples of 12 subjects with pre-MCI and 20 controls. Results The serum levels of 13 proteins were significantly different in patients with AD or MCI compared to controls. Of the 13 proteins, cathepsin D, immunoglobulin E, epidermal growth factor receptor (EGFR), matrix metalloproteinase-9 (MMP-9), von Willebrand factor (vWF), haptoglobin, and phosphorylated Tau-181 (p-Tau181) correlated with all cognitive measures (R2 = −0.69–0.76). The areas under the receiver operating characteristic curve of these seven proteins were 0.71–0.93 for the classification of AD and 0.57–0.95 for the classification of MCI. Higher levels of p-Tau181 were found in the serum of pre-MCI subjects than in the serum of controls. The p-Tau181 serum level might detect AD before symptoms occur (area under the curve 0.85, sensitivity 75%, specificity 81.67%). Conclusions A total of 13 serum proteins showed significant differences between subjects with AD and MCI and healthy controls. The p-Tau181 serum level might be a broadly available and cost-effective biomarker to identify individuals with preclinical AD and assess the severity of AD.
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Affiliation(s)
- Wei Qin
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, National Clinical Research Center for Geriatric Diseases, Beijing, China
| | - Fangyu Li
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, National Clinical Research Center for Geriatric Diseases, Beijing, China
| | - Longfei Jia
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, National Clinical Research Center for Geriatric Diseases, Beijing, China
| | - Qi Wang
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, National Clinical Research Center for Geriatric Diseases, Beijing, China
| | - Ying Li
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, National Clinical Research Center for Geriatric Diseases, Beijing, China
| | - Yiping Wei
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, National Clinical Research Center for Geriatric Diseases, Beijing, China
| | - Yan Li
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, National Clinical Research Center for Geriatric Diseases, Beijing, China
| | - Hongmei Jin
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, National Clinical Research Center for Geriatric Diseases, Beijing, China
| | - Jianping Jia
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, National Clinical Research Center for Geriatric Diseases, Beijing, China
- Beijing Key Laboratory of Geriatric Cognitive Disorders, Capital Medical University, Beijing, China
- Clinical Center for Neurodegenerative Disease and Memory Impairment, Capital Medical University, Beijing, China
- Center of Alzheimer’s Disease, Beijing Institute of Brain Disorders, Collaborative Innovation Center for Brain Disorders, Capital Medical University, Beijing, China
- *Correspondence: Jianping Jia
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Tang MY, Gorin FA, Lein PJ. Review of evidence implicating the plasminogen activator system in blood-brain barrier dysfunction associated with Alzheimer's disease. AGEING AND NEURODEGENERATIVE DISEASES 2022; 2. [PMID: 35156107 PMCID: PMC8830591 DOI: 10.20517/and.2022.05] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
Elucidating the pathogenic mechanisms of Alzheimer’s disease (AD) to identify therapeutic targets has been the focus of many decades of research. While deposition of extracellular amyloid-beta plaques and intraneuronal neurofibrillary tangles of hyperphosphorylated tau have historically been the two characteristic hallmarks of AD pathology, therapeutic strategies targeting these proteinopathies have not been successful in the clinics. Neuroinflammation has been gaining more attention as a therapeutic target because increasing evidence implicates neuroinflammation as a key factor in the early onset of AD disease progression. The peripheral immune response has emerged as an important contributor to the chronic neuroinflammation associated with AD pathophysiology. In this context, the plasminogen activator system (PAS), also referred to as the vasculature’s fibrinolytic system, is emerging as a potential factor in AD pathogenesis. Evolving evidence suggests that the PAS plays a role in linking chronic peripheral inflammatory conditions to neuroinflammation in the brain. While the PAS is better known for its peripheral functions, components of the PAS are expressed in the brain and have been demonstrated to alter neuroinflammation and blood-brain barrier (BBB) permeation. Here, we review plasmin-dependent and -independent mechanisms by which the PAS modulates the BBB in AD pathogenesis and discuss therapeutic implications of these observations.
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Affiliation(s)
- Mei-Yun Tang
- Department of Molecular Biosciences, School of Veterinary Medicine, University of California, Davis, CA 95616, USA
| | - Fredric A Gorin
- Department of Molecular Biosciences, School of Veterinary Medicine, University of California, Davis, CA 95616, USA.,Department of Neurology, School of Medicine, University of California, Davis, CA 95616, USA
| | - Pamela J Lein
- Department of Molecular Biosciences, School of Veterinary Medicine, University of California, Davis, CA 95616, USA
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8
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Liu RM. Aging, Cellular Senescence, and Alzheimer's Disease. Int J Mol Sci 2022; 23:1989. [PMID: 35216123 PMCID: PMC8874507 DOI: 10.3390/ijms23041989] [Citation(s) in RCA: 85] [Impact Index Per Article: 42.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2022] [Revised: 02/07/2022] [Accepted: 02/08/2022] [Indexed: 01/10/2023] Open
Abstract
Aging is the greatest risk factor for late-onset Alzheimer's disease (LOAD), which accounts for >95% of Alzheimer's disease (AD) cases. The mechanism underlying the aging-related susceptibility to LOAD is unknown. Cellular senescence, a state of permanent cell growth arrest, is believed to contribute importantly to aging and aging-related diseases, including AD. Senescent astrocytes, microglia, endothelial cells, and neurons have been detected in the brain of AD patients and AD animal models. Removing senescent cells genetically or pharmacologically ameliorates β-amyloid (Aβ) peptide and tau-protein-induced neuropathologies, and improves memory in AD model mice, suggesting a pivotal role of cellular senescence in AD pathophysiology. Nonetheless, although accumulated evidence supports the role of cellular senescence in aging and AD, the mechanisms that promote cell senescence and how senescent cells contribute to AD neuropathophysiology remain largely unknown. This review summarizes recent advances in this field. We believe that the removal of senescent cells represents a promising approach toward the effective treatment of aging-related diseases, such as AD.
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Affiliation(s)
- Rui-Ming Liu
- Division of Pulmonary, Allergy, and Critical Care, Department of Medicine, School of Medicine, University of Alabama at Birmingham, Birmingham, AL 35294-0006, USA
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9
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Mossanen Parsi M, Duval C, Ariëns RAS. Vascular Dementia and Crosstalk Between the Complement and Coagulation Systems. Front Cardiovasc Med 2021; 8:803169. [PMID: 35004913 PMCID: PMC8733168 DOI: 10.3389/fcvm.2021.803169] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2021] [Accepted: 11/29/2021] [Indexed: 01/12/2023] Open
Abstract
Vascular Dementia (VaD) is a neurocognitive disorder caused by reduced blood flow to the brain tissue, resulting in infarction, and is the second most common type of dementia. The complement and coagulation systems are evolutionary host defence mechanisms activated by acute tissue injury to induce inflammation, clot formation and lysis; recent studies have revealed that these systems are closely interlinked. Overactivation of these systems has been recognised to play a key role in the pathogenesis of neurological disorders such as Alzheimer's disease and multiple sclerosis, however their role in VaD has not yet been extensively reviewed. This review aims to bridge the gap in knowledge by collating current understanding of VaD to enable identification of complement and coagulation components involved in the pathogenesis of this disorder that may have their effects amplified or supressed by crosstalk. Exploration of these mechanisms may unveil novel therapeutic targets or biomarkers that would improve current treatment strategies for VaD.
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Affiliation(s)
| | | | - Robert A. S. Ariëns
- Discovery and Translational Science Department, School of Medicine, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, United Kingdom
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10
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Ziliotto N, Bernardi F, Piazza F. Hemostasis components in cerebral amyloid angiopathy and Alzheimer's disease. Neurol Sci 2021; 42:3177-3188. [PMID: 34041636 DOI: 10.1007/s10072-021-05327-7] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2021] [Accepted: 05/15/2021] [Indexed: 01/17/2023]
Abstract
Increased cerebrovascular amyloid-β (Aβ) deposition represents the main pathogenic mechanisms characterizing Alzheimer's disease (AD) and cerebral amyloid angiopathy (CAA). Whereas an increasing number of studies define the contribution of fibrin(ogen) to neurodegeneration, how other hemostasis factors might be pleiotropically involved in the AD and CAA remains overlooked. Although traditionally regarded as pertaining to hemostasis, these proteins are also modulators of inflammation and angiogenesis, and exert cytoprotective functions. This review discusses the contribution of hemostasis components to Aβ cerebrovascular deposition, which settle the way to endothelial and blood-brain barrier dysfunction, vessel fragility, cerebral bleeding, and the associated cognitive changes. From the primary hemostasis, the process that refers to platelet aggregation, we discuss evidence regarding the von Willebrand factor (vWF) and its regulator ADAMTS13. Then, from the secondary hemostasis, we focus on tissue factor, which triggers the extrinsic coagulation cascade, and on the main inhibitors of coagulation, i.e., tissue factor pathway inhibitor (TFPI), and the components of protein C pathway. Last, from the tertiary hemostasis, we discuss evidence on FXIII, involved in fibrin cross-linking, and on components of fibrinolysis, including tissue-type plasminogen activator (tPA), urokinase-type plasminogen activator (uPA) and its receptor uPA(R), and plasminogen activator inhibitor-1 (PAI-1). Increased knowledge on contributors of Aβ-related disease progression may favor new therapeutic approaches for early modifiable risk factors.
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Affiliation(s)
- Nicole Ziliotto
- CAA and AD Translational Research and Biomarkers Laboratory, School of Medicine and Surgery, University of Milano - Bicocca, Via Cadore 48, 20900, Monza, Italy.
| | - Francesco Bernardi
- Department of Life Sciences and Biotechnology, University of Ferrara, Ferrara, Italy
| | - Fabrizio Piazza
- CAA and AD Translational Research and Biomarkers Laboratory, School of Medicine and Surgery, University of Milano - Bicocca, Via Cadore 48, 20900, Monza, Italy
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11
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Zimnitskaya OV, Mozheyko EY, Petrova MM. Biomarkers of vascular cognitive impairment. КАРДИОВАСКУЛЯРНАЯ ТЕРАПИЯ И ПРОФИЛАКТИКА 2021. [DOI: 10.15829/1728-8800-2021-2677] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022] Open
Abstract
There is currently no approved list of vascular cognitive impairment biomarkers. The main problem for the practitioner in identifying cognitive impairment in patients is the differential diagnosis of Alzheimer's disease, vascular cognitive impairment, and other diseases, which are much less common. Vascular cognitive impairment includes post-stroke dementia, cognitive dysfunction in cardio-and cerebrovascular diseases. Without etiology identification, it is impossible to prescribe adequate treatment. Another challenge is identifying cognitive impairment before dementia develops. This literature review is devoted to the search and critical analysis of candidates for biomarkers of vascular cognitive impairment and the establishment of markers of moderate cognitive dysfunction. The papers were searched for in the Web of Science and PubMed databases. A list of cerebrospinal fluid, plasma, serum and genetic biomarkers was made, allowing for differential diagnosis between vascular impairment and Alzheimer's disease. The markers of moderate cognitive dysfunction, which make it possible to identify cognitive impairment at the pre-dementia stage, were also identified.
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Affiliation(s)
| | | | - M. M. Petrova
- V.F. Voino-Yasenetsky Krasnoyarsk State Medical University
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12
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Rohmann JL, Longstreth WT, Cushman M, Fitzpatrick AL, Heckbert SR, Rice K, Rosendaal FR, Sitlani CM, Psaty BM, Siegerink B. Coagulation factor VIII, white matter hyperintensities and cognitive function: Results from the Cardiovascular Health Study. PLoS One 2020; 15:e0242062. [PMID: 33196677 PMCID: PMC7668572 DOI: 10.1371/journal.pone.0242062] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2019] [Accepted: 10/26/2020] [Indexed: 11/19/2022] Open
Abstract
OBJECTIVE To investigate the relationship between high FVIII clotting activity (FVIII:C), MRI-defined white matter hyperintensities (WMH) and cognitive function over time. METHODS Data from the population-based Cardiovascular Health Study (n = 5,888, aged ≥65) were used. FVIII:C was measured in blood samples taken at baseline. WMH burden was assessed on two cranial MRI scans taken roughly 5 years apart. Cognitive function was assessed annually using the Modified Mini-Mental State Examination (3MSE) and Digit Symbol Substitution Test (DSST). We used ordinal logistic regression models adjusted for demographic and cardiovascular factors in cross-sectional and longitudinal WMH analyses, and adjusted linear regression and linear mixed models in the analyses of cognitive function. RESULTS After adjustment for confounding, higher levels of FVIII:C were not strongly associated with the burden of WMH on the initial MRI scan (OR>p75 = 1.20, 95% CI 0.99-1.45; N = 2,735) nor with WMH burden worsening over time (OR>p75 = 1.18, 95% CI 0.87-1.59; N = 1,527). High FVIII:C showed no strong association with cognitive scores cross-sectionally (3MSE>p75 β = -0.06, 95%CI -0.45 to 0.32, N = 4,005; DSST>p75 β = -0.69, 95%CI -1.52 to 0.13, N = 3,954) or over time (3MSE>p75 β = -0.07,95% CI -0.58 to 0.44, N = 2,764; DSST>p75 β = -0.22, 95% CI -0.97 to 0.53, N = 2,306) after confounding adjustment. INTERPRETATION The results from this cohort study of older adult participants indicate no strong relationships between higher FVIII:C levels and WMH burden or cognitive function in cross-sectional and longitudinal analyses.
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Affiliation(s)
- Jessica L. Rohmann
- Charité –Universitätsmedizin Berlin, Center for Stroke Research Berlin, Berlin, Germany
- Charité –Universitätsmedizin Berlin, Institute of Public Health, Berlin, Germany
| | - W. T. Longstreth
- Department of Neurology, University of Washington, Seattle, WA, United States of America
- Department of Epidemiology, University of Washington, Seattle, WA, United States of America
| | - Mary Cushman
- Department of Medicine, Larner College of Medicine at the University of Vermont, Burlington, VT, United States of America
| | - Annette L. Fitzpatrick
- Department of Epidemiology, University of Washington, Seattle, WA, United States of America
- Department of Family Medicine, University of Washington, Seattle, WA, United States of America
- Department of Global Health, University of Washington, Seattle, WA, United States of America
| | - Susan R. Heckbert
- Department of Epidemiology, University of Washington, Seattle, WA, United States of America
- Cardiovascular Health Research Unit, University of Washington, Seattle, WA, United States of America
| | - Kenneth Rice
- Department of Biostatistics, University of Washington, Seattle, WA, United States of America
| | - Frits R. Rosendaal
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Colleen M. Sitlani
- Cardiovascular Health Research Unit, University of Washington, Seattle, WA, United States of America
| | - Bruce M. Psaty
- Department of Epidemiology, University of Washington, Seattle, WA, United States of America
- Cardiovascular Health Research Unit, University of Washington, Seattle, WA, United States of America
- Department of Medicine, University of Washington, Seattle, WA, United States of America
- Department of Health Services, University of Washington, Seattle, WA, United States of America
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, United States of America
| | - Bob Siegerink
- Charité –Universitätsmedizin Berlin, Center for Stroke Research Berlin, Berlin, Germany
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
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Wang X, Wang L. Screening and Identification of Potential Peripheral Blood Biomarkers for Alzheimer's Disease Based on Bioinformatics Analysis. Med Sci Monit 2020; 26:e924263. [PMID: 32812532 PMCID: PMC7453750 DOI: 10.12659/msm.924263] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2020] [Accepted: 05/28/2020] [Indexed: 12/11/2022] Open
Abstract
BACKGROUND Alzheimer's disease (AD) is the leading cause of dementia worldwide; however, the molecular mechanisms underlying its pathogenesis remain unclear. The present study aimed to discover some potential peripheral blood biomarkers for early detection of patients with AD. MATERIAL AND METHODS Publicly available AD datasets - GSE18309 and GSE97760 - were obtained from the Gene Expression Omnibus database, and limma package from Bioconductor was employed to search for differently expressed genes (DEGs). Weighted correlation network analysis was performed to identify DEGs with highly synergistic changes, and functional annotation of DEGs was performed using gene set enrichment analysis and Metascape. STRING and Cytoscape were used to construct protein-protein interaction networks and analyze the most significant hub genes. Thereafter, the Comparative Toxicogenomics Database (CTD) was used to identify hub genes associated with AD pathology, and Connectivity Map was used to screen small molecule drugs for AD. Finally, hub genes coupled with corresponding predicted miRNAs involved in AD were assessed via TargetScan, and functional annotation of predicted miRNAs was performed using DIANA database. RESULTS Our analyses revealed 5042 DEGs; based on functional analyses, these DEGs were mainly associated with oligosaccharide lipid intermediate biosynthetic process, cyclin binding, signaling pathways regulating pluripotency of ubiquitin mediated proteolysis, and extracellular matrix-receptor interaction. UBB, UBA52, SRC, MMP9, VWF, GP6, and PF4 were identified as the hub genes. The CTD showed that these hub genes are closely related with AD or cognition impairment. CONCLUSIONS The identified hub genes and corresponding miRNAs might be useful as potential peripheral blood biomarkers of AD.
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Zhou Z, Liang Y, Zhang X, Xu J, Lin J, Zhang R, Kang K, Qu H, Zhao C, Zhao M. Fibrinogen and risk of dementia: A systematic review and meta-analysis. Neurosci Biobehav Rev 2020; 112:353-360. [PMID: 32081688 DOI: 10.1016/j.neubiorev.2020.02.022] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2019] [Revised: 01/22/2020] [Accepted: 02/16/2020] [Indexed: 12/19/2022]
Abstract
BACKGROUND The aim of this meta-analysis is to evaluate the association of fibrinogen with risk of dementia and its subtypes. METHODS Embase, Pubmed and Web of Science were retrieved systematically up to February 2019. Standard mean difference (SMD) with 95 % confidence intervals was estimated using random-effects models. RESULTS Sixteen studies involving 3,649 participants were summarized. Patients with all-cause dementia exhibited higher fibrinogen levels than those in non-dementia controls (SMD = 0.90 [0.43;1.36] p < 0.01). Further subgroup analysis revealed a positive association of fibrinogen with vascular dementia (VaD) (SMD = 1.11 [0.45;1.78] p < 0.01) rather than Alzheimer's disease (AD) (SMD = 0.01 [-0.17;0.19]) p = 0.92) and Parkinson's disease dementia (PDD) (SMD = 0.35 [-0.23;0.93] p = 0.24). This correlation was significant in Europeans (SMD = 0.92 [0.34;1.49] p < 0.01), but probably not in Asian based populations (SMD = 1.04 [-0.09;2.17] p = 0.07), and gradually declined with advancing age (60 ≤ age < 70: SMD = 1.22 [0.38;2.06] p < 0.01; 70 ≤ age < 80: SMD = 0.29 [0.04;0.53] p = 0.02; age ≥ 80: SMD = 0.01 [-0.12;0.15] p = 0.84). CONCLUSIONS Plasma fibrinogen is a potential risk factor for all-cause dementia and VaD under the age of 80, and is more obvious in cohorts with people of European descent.
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Affiliation(s)
- Zhike Zhou
- Department of Geriatrics, The First Affiliated Hospital, China Medical University, Shenyang, 110001, Liaoning, PR China
| | - Yifan Liang
- Department of Neurology, The First Affiliated Hospital, China Medical University, Shenyang, 110001, Liaoning, PR China
| | - Xiaoqian Zhang
- Department of Neurology, The First Affiliated Hospital, China Medical University, Shenyang, 110001, Liaoning, PR China
| | - Junjie Xu
- Department of Laboratory Medicine, The First Affiliated Hospital, China Medical University, Shenyang, 110001, Liaoning, PR China
| | - Jueying Lin
- Department of Emergency, Zhongshan Hospital Xiamen University, Xiamen, 361004, Fujian, PR China
| | - Rongwei Zhang
- Department of Geriatrics, The First Affiliated Hospital, China Medical University, Shenyang, 110001, Liaoning, PR China
| | - Kexin Kang
- Department of Geriatrics, The First Affiliated Hospital, China Medical University, Shenyang, 110001, Liaoning, PR China
| | - Huiling Qu
- Department of Neurology, People's Hospital of Liaoning Province, Shenyang, 110016, Liaoning, PR China
| | - Chuansheng Zhao
- Department of Neurology, The First Affiliated Hospital, China Medical University, Shenyang, 110001, Liaoning, PR China.
| | - Mei Zhao
- Department of Cardiology, The Shengjing Affiliated Hospital, China Medical University, Shenyang, 110004, Liaoning, PR China.
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