Plasma exosome proteomics reveals the pathogenesis mechanism of post stroke cognitive impairment in Chinese people
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo Sapiens
SUBMITTER: 
Weiwei Ji
PROVIDER: PXD028200 | iProX | Thu Sep 02 00:00:00 BST 2021
REPOSITORIES: iProX
Publications
Plasma exosome proteomics reveals the pathogenesis mechanism of post-stroke cognitive impairment.
Qi Baoyun B Kong Lingbo L Lai Xinxing X Wang Linshuang L Liu Fei F Ji Weiwei W Wei Dongfeng D
Aging 20230520 10
Exploration and utilization of exosome biomarkers and their related functions provide the possibility for the diagnosis and treatment of post-stroke cognitive impairment (PSCI). To identify the new diagnostic and prognostic biomarkers of plasma exosome were uzed label-free quantitative proteomics and biological information analysis in PSCI patients. Behavioral assessments were performed, including the Mini-Mental Status Examination (MMSE), the Montreal Cognitive Assessment (MoCA), the Barthel in ...[more]
Similar Datasets
Project description:Exploration and utilization of exosome biomarkers and their related functions provide the possibility for the diagnosis and treatment of post-stroke cognitive impairment (PSCI). To identify the new diagnostic and prognostic biomarkers of plasma exosome were uzed label-free quantitative proteomics and biological information analysis in PSCI patients. Behavioral assessments were performed, including the Mini-Mental Status Examination (MMSE), the Montreal Cognitive Assessment (MoCA), the Barthel index, the Morse Fall Seale (MFS) between control group (n = 10) and PSCI group (n = 10). The blood samples were collected to analyse the biomarker and differentially expressed proteins of plasma exosome using label-free quantitative proteomics and biological information. The exosomes marker proteins were determined by Western blot. The exosome morphology was observed by transmission electron microscopy. The scores of MMSE and MoCA were significantly decreased in the PSCI group. The PT% and high-density lipoprotein decreased and the INR ratio increased in PSCI group. The mean size of exosome was approximately 71.6 nm and the concentration was approximately 6.8E+7 particles/mL. Exosome proteomics identified 259 differentially expressed proteins. The mechanisms of cognitive impairment are related to regulate the degradation of ubiquitinated proteins, calcium dependent protein binding, cell adhesive protein binding, formation of fibrin clot, lipid metabolism and ATP-dependent degradation of ubiquitinated proteins in plasma exosome of PSCI patients. Plasma levels of YWHAZ and BAIAP2 were significantly increased while that of IGHD, ABCB6 and HSPD1 were significantly decreased in PSCI patients. These proteins might be target-related proteins and provide global insights into pathogenesis mechanisms of PSCI at plasma exosome proteins level.
| S-EPMC10258006 | biostudies-literature
Project description:BackgroundStroke is a leading cause of death and disability worldwide. Despite the prevalence and associated burden of cognitive impairment post-stroke, there is uncertainty regarding optimal cognitive rehabilitation for people post-stroke. This study aimed to assess whether a multicomponent intervention, called OptiCogs, is feasible, acceptable, and safe for people with cognitive impairment post-stroke. A secondary aim was to explore changes in cognitive function, fatigue, quality of life, physical function, and occupational performance, from pre-intervention to post-intervention.MethodsA feasibility study was conducted where people post-stroke with cognitive impairment enrolled in a 6-week multicomponent intervention. The primary outcomes recorded included response rate, recruitment rate, retention rate, adherence to the intervention protocol, adverse events, and acceptability of the intervention to people post-stroke. Secondary outcomes included (i) change in cognitive functioning using the Addenbrooke's Cognitive Examination III, (ii) fatigue using the Fatigue Severity scale, (iii) quality of life using the Stroke Specific Quality of Life scale (iv) physical function using the patient-reported outcomes measurement information system, and (v) patient-reported occupational performance using the Canadian Occupational Performance Measure. The Consolidated Standards of Reporting Trials extension reporting guidelines were followed, for pilot and feasibility studies, to standardize the conduct and reporting of this study.ResultsThe response rate was 10.9%. Nine eligible participants were enrolled during the 4-month recruitment period, with eight participants completing the entire 6-week intervention, as well as the pre- and post-intervention outcome measures. There were no reported adverse events. Participants were satisfied with the intervention and found it acceptable overall. Results of the secondary outcomes were promising for cognitive function (ACE III, pre: 63.3 ± 23.9 to post: 69 ± 24.6), fatigue (FSS, pre: 52.5 ± 7.3 to post: 45.6 ± 7.2), quality of life (SSQoL, pre: 131.0 ± 26.3 to post: 169.9 ± 15.3), physical function (PROMIS-PF, pre: 15.5 ± 6.3 to post: 15.8 ± 5.3), and occupational performance (COPM performance, pre: 9.3 ± 2.3 to post: 22.9 ± 4.2) and COPM satisfaction, pre: 9.9 ± 2.1 to post: 22.7 ± 3.5).ConclusionPreliminary results suggest low-modest recruitment and high retention rates for the OptiCogs intervention. Changes in cognitive function, fatigue, quality of life, and self-reported occupational performance show improvement from pre- to post-intervention. These potential benefits require further testing in a larger pilot trial.Trial registrationNCT05414539.
| S-EPMC10583340 | biostudies-literature
Project description:Background: Post-stroke cognitive impairment (PSCI) affects more than one-third of stroke patients, and causes much greater harm to long-term function than the initial brain damage. No conventional Western medications have shown convincing clinical effectiveness for treating PSCI. Research shows that Traditional Chinese medicine (TCM) can improve cognitive function in patients. However, the clinical efficacy and safety remain controversial. The aim of this study was to examine the effectiveness and harmful effects of TCMs in the treatment of PSCI. Method: We searched seven databases and two clinical registration websites for randomized controlled trials (RCTs). The revised Cochrane risk of bias tool (RoB 2.0) was used to evaluate the methodological quality and RevMan 5.4 was used for data analysis. This study has been submitted to PROSPERO with registration number is CRD42020149299. Results: We included 34 studies in this review. The results of this study showed that TCM adjuvant therapy improved scores on the MoCA [MD = 2.55, 95% CI (1.56, 3.53), p < 0.00001; MD = 3.07, 95% CI (1.98, 4.17), p < 0.00001 at treatment duration of <3 and 3 months, respectively], MMSE [MD = 2.55, 95% CI (1.99, 3.10), p < 0.00001; MD = 2.53, 95% CI (1.59, 3.47), p < 0.00001; MD = 2.91, 95% CI (1.26, 4.56), p = 0.0006; MD = 3.11, 95% CI (-0.04, 6.27), p = 0.05 at treatment duration of <3, 3, 4, and 6 months, respectively], and BI [MD = 7.34, 95% CI (3.83, 10.85), p < 0.0001; MD = 8.98, 95% CI (4.76, 13.21), p < 0.0001 at treatment duration of <3 and 3 months, respectively] and reduced scores on the ADL (MD = -8.64, 95% CI (-9.83, -7.45), p < 0.00001; MD = -2.00, 95% CI (-2.94, -1.06), p < 0.0001 at treatment duration of 3 and 4 months, respectively], NIHSS [MD = -2.48, 95% CI (-4.97, 0.00), p = 0.05; MD = -3.81, 95% CI (-6.21, -1.40), p = 0.002 at treatment duration of <3 and 3 months, respectively], and CSS [MD = -2.47, 95% CI (-3.49, -1.45), p < 0.00001 at a treatment duration of 3 months]. No serious adverse reactions were observed. Conclusion: Despite the significant positive results, the present evidence supports, to a limited extent because of the methodological flaws and herbal heterogeneity, that TCM adjuvant therapy can be used for patients with PSCI. While, further rigorous RCTs are warranted to confirm the efficacy and safety of TCM. Systematic Review Registration: https://www.crd.york.ac.uk/prospero, identifier CRD42020149299.
| S-EPMC8883343 | biostudies-literature
Project description:Background: Together with cerebral small vessel disease (CSVD), large vessel atherosclerosis is considered to be an equally important risk factor in the progression of vascular cognitive impairment. This article aims to investigate whether carotid atherosclerotic calcification is associated with the increased risk of post-stroke cognitive impairment (PSCI). Methods: A total of 128 patients (mean age: 62.1 ± 12.2 years, 37 women) suffering from ischemic stroke underwent brain/neck computer tomography angiography examination. The presence and characteristic of carotid calcification (size, number and location) were analyzed on computer tomography angiography. White matter hyperintensity (WMH) was assessed using Fazekas scales. PSCI was diagnosed based on a battery of neuropsychological assessments implemented 6-12 months after stroke. Results: Among 128 patients, 26 developed post-stroke dementia and 96 had carotid calcification. Logistic regression found carotid calcification (odds ratio [OR] = 7.15, 95% confidence interval [CI]: 1.07-47.69) and carotid artery stenosis (OR = 6.42, 95% CI: 1.03-40.15) both significantly increased the risk for post-stroke dementia. Moreover, multiple, thick/mixed, and surface calcifications exhibited an increasing trend in PSCI (P trend = 0.004, 0.016, 0.045, respectively). The prediction model for post-stroke dementia including carotid calcification (area under curve = 0.67), WMH (area under curve = 0.67) and other covariates yielded an area under curve (AUC) of 0.90 (95% CI: 0.82-0.99). Conclusion: Our findings demonstrated that the quantity and location of carotid calcifications were independent indicators for PSCI. The significant role of large vessel atherosclerosis in PSCI should be concerned in future study.
| S-EPMC8185032 | biostudies-literature
Project description:BackgroundThe aim of this study is to investigate the associations between post-stroke cognitive impairment (PSCI) severity and reactive astrogliosis (RA) extent on normalized 18F-THK-5351 positron-emission tomography (PET) imaging in amyloid-negative patients with first-ever stroke.MethodsWe prospectively enrolled 63 amyloid-negative patients with first-ever stroke. Neurocognitive evaluation, MRI, 18F-THK-5351, and 18F-florbetapir PET were performed around 3 months after stroke. The 18F-THK-5351 uptake intensity was normalized using a signal distribution template to obtain the Z-SUM scores as the RA extent in the whole brain and cerebral hemisphere ipsilateral to stroke lesion. We evaluated stroke volume, leukoaraiosis, and brain atrophy on MRI. We used a comprehensive neurocognitive battery to obtain composite cognitive scores, and defined PSCI as a general cognitive function score < - 1. We analyzed the influence of Z-SUM scores on PSCI severity after adjusting for demographic, vascular, and neurodegenerative variables.ResultsTwenty-five of 63 stroke patients had PSCI. Patients with PSCI had older age, lower education, and more severe cortical atrophy and total Z-SUM scores. Total Z-SUM scores were significantly associated with general cognitive and executive functions at multiple regression models. Path analyses showed that stroke can exert cognitive influence directly by stroke itself as well as indirectly through RA, including total and ipsilateral Z-SUM scores, in patients with either right or left hemisphere stroke.ConclusionThe patterns and intensity of 18F-THK-5351 uptake in amyloid-negative patients with first-ever stroke were associated with PSCI manifestations, which suggests that RA presents a modulating effect in PSCI development.
| S-EPMC7568828 | biostudies-literature
Project description:ImportanceSecondary prevention interventions to reduce post-stroke cognitive impairment (PSCI) can be aided by the early identification of high-risk individuals who would benefit from risk factor modification.ObjectiveTo develop and evaluate a predictive model to identify patients at increased risk of PSCI over 5 years using data easily accessible from electronic health records.DesignCohort study with patients enrolled between 2003-2016 with follow-up through 2022.SettingPrimary care practices affiliated with two academic medical centers.ParticipantsIndividuals 45 years or older, without prior stroke or prevalent cognitive impairment, with primary care visits and an incident ischemic stroke between 2003-2016 (development/internal validation cohort) or 2010-2022 (external validation cohort).ExposuresPredictors of PSCI were ascertained from the electronic health record.Main outcomeThe outcome was incident dementia/cognitive impairment within 5 years and beginning 3 months following stroke, ascertained using ICD-9/10 codes. For model variable selection, we considered potential predictors of PSCI and constructed 400 bootstrap samples with two-thirds of the model derivation sample. We ran 10-fold cross-validated Cox proportional hazards models using a least absolute shrinkage and selection operator (LASSO) penalty. Variables selected in >25% of samples were included.ResultsThe analysis included 332 incident diagnoses of PSCI in the development cohort (n=3,741), and 161 and 128 incident diagnoses in the internal (n=1,925) and external (n=2,237) validation cohorts. The c-statistic for predicting PSCI was 0.731 (95% CI: 0.694-0.768) in the internal validation cohort, and 0.724 (95% CI: 0.681-0.766) in the external validation cohort. A risk score based on the beta coefficients of predictors from the development cohort stratified patients into low (0-7 points), intermediate (8-11 points), and high (12-35 points) risk groups. The hazard ratios for incident PSCI were significantly different by risk categories in internal (High, HR: 6.2, 95% CI 4.1-9.3; Intermediate, HR 2.7, 95% CI: 1.8-4.1) and external (High, HR: 6.1, 95% CI: 3.9-9.6; Intermediate, HR 2.8, 95% CI: 1.9-4.3) validation cohorts.Conclusions and relevanceFive-year risk of PSCI can be accurately predicted using routinely collected data. Model output can be used to risk stratify and identify individuals at increased risk for PSCI for preventive efforts.
| S-EPMC10863024 | biostudies-literature
Project description:We investigate the single cell transcriptome of hippocampus in both groups. A total of 27,069 cells were identified as 13 cell types, belong to neuronal, glial and vascular lineages. Then the cell-specific molecular changes and function in PSCI were analyzed.
2023-04-02 | GSE171393 | GEO
Project description:Background and objectives Post-stroke cognitive impairment (PSCI) occurs in up to 50% of patients with acute ischemic stroke (AIS). Thus, the prediction of cognitive outcomes in AIS may be useful for treatment decisions. This PSCI cohort study aimed to determine the applicability of a machine learning approach for predicting PSCI after stroke. Methods This retrospective study used a prospective PSCI cohort of patients with AIS. Demographic features, clinical characteristics, and brain imaging variables previously known to be associated with PSCI were included in the analysis. The primary outcome was PSCI at 3–6 months, defined as an adjusted z-score of less than − 2.0 standard deviation in at least one of the four cognitive domains (memory, executive/frontal, visuospatial, and language), using the Korean version of the Vascular Cognitive Impairment Harmonization Standards-Neuropsychological Protocol (VCIHS-NP). We developed four machine learning models (logistic regression, support vector machine, extreme gradient boost, and artificial neural network) and compared their accuracies for outcome variables. Results A total of 951 patients (mean age 65.7 ± 11.9; male 61.5%) with AIS were included in this study. The area under the curve for the extreme gradient boost and the artificial neural network was the highest (0.7919 and 0.7365, respectively) among the four models for predicting PSCI according to the VCIHS-NP definition. The most important features for predicting PSCI include the presence of cortical infarcts, mesial temporal lobe atrophy, initial stroke severity, stroke history, and strategic lesion infarcts. Conclusion Our findings indicate that machine-learning algorithms, particularly the extreme gradient boost and the artificial neural network models, can best predict cognitive outcomes after ischemic stroke. Supplementary Information The online version contains supplementary material available at 10.1186/s13195-023-01289-4.
| S-EPMC10468853 | biostudies-literature
Project description:ObjectiveProton magnetic resonance spectroscopy (1H-MRS) was applied in this study to detect metabolite changes in the brain of post-stroke cognitive impairment (PSCI) and normal volunteers. The levels of N-acetylaspartate (NAA) and creatinine (Cr) and in the frontal lobe, hippocampus and cingulate gyrus were measured to distinguish patients with post-stroke cognitive impairment (PSCI) and normal control group (NC). The relationship between them and cognitive function was explored and a critical value of the metabolite ratio was predicted. This study may serve as a reference for the diagnosis of cognitive dysfunction after stroke.MethodsA total of 46 patients with PSCI (PSCI group, all patients are unilateral cerebral infarction or intracerebral haemorrhage) were screened by the Mini-Mental Status Examination (MMSE), and 35 healthy volunteers were selected as normal control group (NC group). The general information of gender, age, and education level was matched between the two groups. Two groups of subjects were examined using MRS and evaluated for cognitive function using the MMSE test and the Montreal Cognitive Assessment Scale (MoCA). The correlation between MRS and neurobehavioral scale (MMSE test and MoCA scale) was analysed, and the possible demarcation points of the brain metabolism of PSCI were evaluated.ResultThe MMSE and MoCA scores of patients with PSCI were lower significantly when compared with those of the NC group (P < 0.05). The NAA/Cr values of the bilateral hippocampus, bilateral frontal lobe and bilateral anterior and posterior cingulate gyrus in the PSCI group were lower than those in the NC group (P < 0.05). The NAA/Cr cut-off value for the right frontal lobe was 1.533, and the NAA/Cr sensitivity, specificity and Youden index for the right frontal lobe were 0.943, 0.935, and 0.878.ConclusionNAA/Cr values in the MRS bilateral frontal, bilateral hippocampus and bilateral anterior and posterior cingulate gyrus were reduced in the cognitively impaired post-stroke patients compared to the normal control group. MRS was also found to be correlated with the score of neurobehavioral scale (MMSE test and MoCA scale) and the combination of the two could evaluate cognitive dysfunction more comprehensively and objectively. NAA/Cr value of the right frontal lobe < 1.533 indicated that PSCI may occur. In accordance with this cut-off point, PSCI could be detected as early as possible and timely intervention could be carried out.
| S-EPMC10598682 | biostudies-literature
Project description:Background: Non-linguistic cognitive training has been suggested to improve the communication skills of patients with post-stroke aphasia (PSA). However, the association between language and non-linguistic cognitive functions is not fully understood. In this study, we used the Loewenstein Occupational Therapy Cognitive Assessment (LOTCA) to evaluate the characteristics of non-linguistic cognitive impairments in Chinese PSA patients. Methods: A total of 86 stroke patients were recruited in this study. Language and non-linguistic cognitive impairments were evaluated by the Western Aphasia Battery (WAB) and LOTCA, respectively. The patients were divided into two groups (PSA and non-PSA), and the Chinese norm (the data came from 44 Chinese individuals without neurological disorders in a previous study) was used as the control group. The LOTCA scores were compared among the three groups. Patients in the PSA group were subdivided into the fluent aphasia group (FAG) and the non-FAG according to the Chinese aphasia fluency characteristic scale. The LOTCA scores were also compared between the PSA subdivisions. Potential confounders were adjusted in the analysis of covariance. Partial correlation analysis between the subscores of WAB and LOTCA was also performed. Results: The total LOTCA scores in the PSA group (75.11 ± 17.08) were significantly lower compared with scores in the non-PSA (96.80 ± 7.75, P < 0.001) and the control group (97.65 ± 16.24, P < 0.001). The PSA group also had lower orientation, visual perception (VP), spatial perception (SP), visuomotor organization, thinking operation, and attention scores. The total LOTCA, orientation, VP, SP, and MP scores were lower in the non-FAG (69.24 ± 18.06, 8.62 ± 5.09, 12.76 ± 2.47, 7.48 ± 3.01, and 9.62 ± 2.25, respectively) compared with the FAG (80.36 ± 14.07, 12.14 ± 3.99, 14.09 ± 1.93, 9.68 ± 3.01, 10.55 ± 1.63, respectively, P's < 0.05). The aphasia quotient was positively correlated with the total score of LOTCA and scores of orientation, VP, SP, and MP (r = 0.710, 0.744, 0.565, 0.597, and 0.616; P < 0.001). Conclusion: Compared with stroke patients without aphasia, patients with PSA often have more extensive and serious non-linguistic cognitive impairments. Patients with non-fluent aphasia often present with serious cognitive impairments than those with fluent aphasia, especially the impairments of orientation and SP. Non-linguistic cognitive impairments correlate with language impairments in aphasia.
| S-EPMC7561418 | biostudies-literature