Fibulin-5: a novel biomarker for evaluating severity and predicting prognosis in patients with acute intracerebral haemorrhage

The extracellular matrix as modifier of neuroinflammation and recovery in ischemic stroke and intracerebral hemorrhage

Stroke is the second leading cause of death worldwide and has two major subtypes: ischemic stroke and hemorrhagic stroke. Neuroinflammation is a pathological hallmark of ischemic stroke and intracerebral hemorrhage (ICH), contributing to the extent of brain injury but also in its repair. Neuroinflammation is intricately linked to the extracellular matrix (ECM), which is profoundly altered after brain injury and in aging. In the early stages after ischemic stroke and ICH, immune cells are involved in the deposition and remodeling of the ECM thereby affecting processes such as blood-brain barrier and cellular integrity. ECM components regulate leukocyte infiltration into the central nervous system, activate a variety of immune cells, and induce the elevation of matrix metalloproteinases (MMPs) after stroke. In turn, excessive MMPs may degrade ECM into components that are pro-inflammatory and injurious. Conversely, in the later stages after stroke, several ECM molecules may contribute to tissue recovery. For example, thrombospondin-1 and biglycan may promote activity of regulatory T cells, inhibit the synthesis of proinflammatory cytokines, and aid regenerative processes. We highlight these roles of the ECM in ischemic stroke and ICH and discuss their potential cellular and molecular mechanisms. Finally, we discuss therapeutics that could be considered to normalize the ECM in stroke. Our goal is to spur research on the ECM in order to improve the prognosis of ischemic stroke and ICH.

Biomarkers for prognostic functional recovery poststroke: A narrative review

Background and objective: Prediction of poststroke recovery can be expressed by prognostic biomarkers that are related to the pathophysiology of stroke at the cellular and molecular level as well as to the brain structural and functional reserve after stroke at the systems neuroscience level. This study aimed to review potential biomarkers that can predict poststroke functional recovery. Methods: A narrative review was conducted to qualitatively summarize the current evidence on biomarkers used to predict poststroke functional recovery. Results: Neurophysiological measurements and neuroimaging of the brain and a wide diversity of molecules had been used as prognostic biomarkers to predict stroke recovery. Neurophysiological studies using resting-state electroencephalography (EEG) revealed an interhemispheric asymmetry, driven by an increase in low-frequency oscillation and a decrease in high-frequency oscillation in the ipsilesional hemisphere relative to the contralesional side, which was indicative of individual recovery potential. The magnitude of somatosensory evoked potentials and event-related desynchronization elicited by movement in task-related EEG was positively associated with the quantity of recovery. Besides, transcranial magnetic stimulation (TMS) studies revealed the potential values of using motor-evoked potentials (MEP) and TMS-evoked EEG potentials from the ipsilesional motor cortex as prognostic biomarkers. Brain structures measured using magnetic resonance imaging (MRI) have been implicated in stroke outcome prediction. Specifically, the damage to the corticospinal tract (CST) and anatomical motor connections disrupted by stroke lesion predicted motor recovery. In addition, a wide variety of molecular, genetic, and epigenetic biomarkers, including hemostasis, inflammation, tissue remodeling, apoptosis, oxidative stress, infection, metabolism, brain-derived, neuroendocrine, and cardiac biomarkers, etc., were associated with poor functional outcomes after stroke. However, challenges such as mixed evidence and analytical concerns such as specificity and sensitivity have to be addressed before including molecular biomarkers in routine clinical practice. Conclusion: Potential biomarkers with prognostic values for the prediction of functional recovery after stroke have been identified; however, a multimodal approach of biomarkers for prognostic prediction has rarely been studied in the literature. Future studies may incorporate a combination of multiple biomarkers from big data and develop algorithms using data mining methods to predict the recovery potential of patients after stroke in a more precise way.

Plasma Fibulin-5 Levels as an Independent Predictor of a Poor Outcome after an Aneurysmal Subarachnoid Hemorrhage

Aneurysmal subarachnoid hemorrhage (SAH) is a poor-outcome disease with a delayed neurological exacerbation. Fibulin-5 (FBLN5) is one of matricellular proteins, some of which have been involved in SAH pathologies. However, no study has investigated FBLN5's roles in SAH. This study was aimed at examining the relationships between serially measured plasma FBLN5 levels and neurovascular events or outcomes in 204 consecutive aneurysmal SAH patients, including 77 patients (37.7%) with poor outcomes (90-day modified Rankin Scale 3-6). Plasma FBLN5 levels were not related to angiographic vasospasm, delayed cerebral ischemia, and delayed cerebral infarction, but elevated levels were associated with severe admission clinical grades, any neurological exacerbation and poor outcomes. Receiver-operating characteristic curves indicated that the most reasonable cut-off values of plasma FBLN5, in order to differentiate 90-day poor from good outcomes, were obtained from analyses at days 4-6 for all patients (487.2 ng/mL; specificity, 61.4%; and sensitivity, 62.3%) and from analyses at days 7-9 for only non-severe patient (476.8 ng/mL; specificity, 66.0%; and sensitivity, 77.8%). Multivariate analyses revealed that the plasma FBLN5 levels were independent determinants of the 90-day poor outcomes in both all patients' and non-severe patients' analyses. These findings suggest that the delayed elevation of plasma FBLN5 is related to poor outcomes, and that FBLN5 may be a new molecular target to reveal a post-SAH pathophysiology.

The disturbance of lipid metabolism is correlated with neuropsychiatric symptoms in patients with Parkinson's disease

OBJECTIVE

We aimed to identify the detailed relationships between serum lipid levels and neuropsychiatric symptoms in patients with Parkinson's disease (PD).

METHODS

Consecutive PD patients and healthy controls were recruited and demographic data were collected. The disease stages of PD patients were assessed using Hoehn-Yahr scale while neuropsychiatric symptoms were determined using Hamilton depression rating scale (HAMD), Hamilton anxiety rating scale (HAMA), and mini-mental state examination scale. Fast serum samples were obtained and the serum levels of lipids were identified. Linear regression analyses and correlation analyses were performed to explore the relationships between serum lipid levels and neuropsychiatric symptoms.

RESULTS

The serum levels of triglyceride had significantly decreased while the levels of HDL-c and lipoprotein a had increased in PD patients. Linear regression analyses confirmed that the levels of triglyceride were mainly correlated with age and HAMA score, the levels of HDL-c were correlated with disease duration and gender, and the levels of lipoprotein a were correlated with HAMD score. Correlation analyses further confirmed that the levels of triglyceride were negatively correlated with HAMA score when the levels of lipoprotein a were negatively correlated with HAMD score.

CONCLUSIONS

Lipid metabolism is significantly correlated with neuropsychiatric disorders in PD patients.

Lipid metabolic dysregulation is involved in Parkinson's disease dementia

Dementia is very common in the late stage of patient with Parkinson's disease (PD). We aim to explore its underlying pathogenesis and identify candidate biomarkers using untargeted metabolomics analysis. Consecutive PD patients and healthy controls were recruited. Clinical data were assessed and patients were categorized into Parkinson's disease without dementia (PDND) and Parkinson's disease dementia (PDD). Fast plasma samples were obtained and untargeted liquid chromatography-mass spectrometry-based metabolomics analysis was performed. Based on the identified differentially-expressed metabolites from the metabolomics analysis, multivariate linear regression analyses and receiver operating characteristic (ROC) curves were further employed. According to the clinical data, the mean ages of PDND and PDD patients were significantly higher than those of healthy controls. The incidence of hypercholesterolemia was decreased in PDD patients. PDD patients also had lower levels of triglyceride, low-density lipoprotein cholesterol, and apolipoprotein B. There were 24 and 57 differentially expressed metabolites in PDD patients when compared with the healthy controls and PDND patients from the metabolomics analysis. Eleven lipid metabolites were simultaneously decreased between these two groups, and can be further subcategorized into fatty acyls, glycerolipids, glycerophospholipids, sphingolipids, and prenol lipids. The plasma levels of the eleven metabolites were positively correlated with MMSE score and can be candidate biomarkers for PDD patients with areas under the curve ranging from 0.724 to 0.806 based on the ROC curves. Plasma lipoproteins are significantly lower in PDD patients. A panel of eleven lipid metabolites were also decreased and can be candidate biomarkers for the diagnosis of PDD patients. Lipid metabolic dysregulation is involved in the pathogenesis of Parkinson's disease dementia.

Ischemia-modified albumin and fibulin-5 as diagnostic and prognostic markers for acute cerebrovascular disease

Background

Fibulin-5 and ischemia-modified albumin (IMA) levels increase in acute phase of cerebrovascular diseases, yet data regarding their levels in various stroke subtypes and correlation with severity and prognosis are still insufficient. This work aims to evaluate serum IMA and fibulin-5 as markers for early detection and predicting prognosis in acute cerebrovascular disease.

Method

This case-control study was done on 100 patients with first time stroke, assessed by the National Institute of Health Stroke Scale (NIHSS) and Glasgow Coma Scale (GCS) within the first 24 h after stroke event, lesion volume was calculated, serum fibulin-5 and IMA levels were measured in the first few hours of stroke, and their levels were compared with levels measured in 75 control subjects. Three months later, stroke patients were assessed by the modified Rankin Scale (MRS).

Results

Fibulin-5 and IMA were significantly higher in the patient than in the control group and were positively correlated with lesion volume and NIHSS score but inversely correlated with GCS score. Fibulin-5 was statistically higher in hemorrhage group, whereas IMA was statistically higher in infarction group. MRS score was positively correlated with fibulin-5 levels at onset of stroke but not with IMA.

Conclusion

Fibulin-5 and ischemia-modified albumin are increased during the acute stroke phase and correlated with severity of stroke, but only fibulin-5 shows significant correlation with prognosis.

Metabolomics profiling reveals altered lipid metabolism and identifies a panel of lipid metabolites as biomarkers for Parkinson's disease related anxiety disorder

OBJECTIVES

Anxiety disorder is a common non-motor symptom in patient with Parkinson's disease (PD). We aimed to explore its pathogenesis and identify plasma biomarkers using untargeted metabolomics analysis.

METHODS

Consecutive PD patients and healthy controls were recruited. Clinical data were assessed and patients with Parkinson's disease related anxiety disorder (PDA) were recognized. Fast plasma samples were obtained and untargeted liquid chromatography-mass spectrometry-based metabolomics analysis was performed. Based on the differentially expressed metabolites from the above metabolomics analysis, correlation analyses and receiver operating characteristic curves (ROC) were further employed.

RESULTS

According to the clinical data, PDA patients had lower plasma levels of total cholesterol, triglyceride, low-density lipoprotein cholesterol, and apolipoprotein B. There were thirty-nine differentially expressed metabolites in PDA patients when compared with the other two groups from the metabolomics analysis, respectively. Fourteen lipid metabolites were simultaneously altered between these two groups, and all of them were significantly decreased. They can be further subcategorized into fatty acyls, glycerolipids, sterol lipids, sphingolipids, and prenol lipids. The plasma levels of thirteen metabolites were negatively correlated with HAMA scores except 10-oxo-nonadecanoic acid. Based on the ROC curves, the fourteen lipid metabolites can be diagnostic biomarkers for PDA patients separately and the areas under the curve of the fourteen lipid metabolites ranged from 0.681 to 0.798.

CONCLUSIONS

Significantly lower plasma lipoproteins can be found in PDA patients. A panel of fourteen lipid metabolites were also significantly decreased and can be clinical biomarkers for the diagnosis of PDA patients.

Integrated Metabolomics and Proteomics Analysis Reveals Plasma Lipid Metabolic Disturbance in Patients With Parkinson's Disease

Parkinson’s disease (PD) is a common neurodegenerative disease in the elderly with a pathogenesis that remains unclear. We aimed to explore its pathogenesis through plasma integrated metabolomics and proteomics analysis. The clinical data of consecutively recruited PD patients and healthy controls were assessed. Fasting plasma samples were obtained and analyzed using metabolomics and proteomics methods. After that, differentially expressed metabolites and proteins were identified for further bioinformatics analysis. No significant difference was found in the clinical data between these two groups. Eighty-three metabolites were differentially expressed in PD patients identified by metabolomics analysis. These metabolites were predominately lipid and lipid-like molecules (63%), among which 25% were sphingolipids. The sphingolipid metabolism pathway was enriched and tended to be activated in the following KEGG pathway analysis. According to the proteomics analysis, forty proteins were identified to be differentially expressed, seven of which were apolipoproteins. Furthermore, five of the six top ranking Gene Ontology terms from cellular components and eleven of the other fourteen Gene Ontology terms from biological processes were directly associated with lipid metabolism. In KEGG pathway analysis, the five enriched pathways were also significantly related with lipid metabolism (p < 0.05). Overall, Parkinson’s disease is associated with plasma lipid metabolic disturbance, including an activated sphingolipid metabolism and decreased apolipoproteins.

Blood Biomarkers for Stroke Diagnosis and Management

Biomarkers are objective indicators used to assess normal or pathological processes, evaluate responses to treatment and predict outcomes. Many blood biomarkers already guide decision-making in clinical practice. In stroke, the number of candidate biomarkers is constantly increasing. These biomarkers include proteins, ribonucleic acids, lipids or metabolites. Although biomarkers have the potential to improve the diagnosis and the management of patients with stroke, there is currently no marker that has demonstrated sufficient sensitivity, specificity, rapidity, precision, and cost-effectiveness to be used in the routine management of stroke, thus highlighting the need for additional work. A better standardization of clinical, laboratory and statistical procedures between centers is indispensable to optimize biomarker performance. This review focuses on blood biomarkers that have shown promise for translation into clinical practice and describes some newly reported markers that could add to routine stroke care. Avenues for the discovery of new stroke biomarkers and future research are discussed. The description of the biomarkers is organized according to their expected application in clinical practice: diagnosis, treatment decision, and outcome prediction.

Integrated Analysis Reveals Altered Lipid and Glucose Metabolism and Identifies NOTCH2 as a Biomarker for Parkinson's Disease Related Depression

Depression is a common comorbidity in Parkinson's disease (PD) but is underdiagnosed. We aim to investigate the altered metabolic pathways of Parkinson's disease-related depression (PDD) in plasma and to identify potential biomarkers for clinical diagnosis. Consecutive patients with PD were recruited, clinically assessed, and patients with PDD identified. Fasting plasma samples were collected from 99 patients and differentially expressed metabolites and proteins between patients with PDD and PD were identified using non-targeted liquid chromatography-mass spectrometry (LC-MS)-based metabolomics and tandem mass tag (TMT)-based proteomics analysis, followed by an integrated analysis. Based on the above results, enzyme-linked immune sorbent assay (ELISA) tests were then performed to identify potential biomarkers for PDD. In clinics, patients with PDD suffered less hypertension and had lower serum low-density lipoprotein cholesterol and apolipoprotein B levels when compared to the other patients with PD. A total of 85 differentially expressed metabolites were identified in metabolomics analysis. These metabolites were mainly lipids and lipid-like molecules, involved in lipid and glucose metabolic pathways. According to proteomics analysis, 17 differentially expressed proteins were identified, and 12 metabolic pathways were enriched, which were predominantly related to glucose metabolism. Integrated analysis indicated that altered lipid and glucose metabolism in PDD may induce cellular injury through oxidative stress. Additionally, plasma levels of several proteins were confirmed to be significantly altered and correlated with depressive severity. NOTCH2 may be a potential blood biomarker for PDD, with an optimal cut-off point of 0.91 ng/ml, a sensitivity value of 95.65%, and a specificity value of 81.58%. Depressive symptoms are associated with lipid and glucose metabolism in patients with PD and NOTCH2 may be a potential blood biomarker for the clinical diagnosis of PDD.

Serum Butyrylcholinesterase Activity: A Biomarker for Parkinson's Disease and Related Dementia

Objective

This study aim to determine changes of serum butyrylcholinesterase (BChE) activity in PD patients and related dementia.

Patients and Methods

Consecutive PD patients and healthy controls were included and clinical data were collected. Fast serum BChE activity was determined and compared between healthy controls and PD patients. Independent risk factors were performed for BChE activity, PD, and related dementia. The relationship between BChE activity and disease severity was also evaluated. Receiver operating characteristic (ROC) curves were obtained to explore serum BChE activity in distinguishing PD patients and related dementia.

Results

Serum BChE activity mainly independently correlated with gender, albumin, triglyceride, body mass index, and PD. Serum BChE activity decreased in PD patients compared with healthy controls. Based on the ROC curve, the optimal cut-off point was 6864.08 IU/L for distinguishing PD patients, and the sensitivity and specificity values were 61.8% and 72.1%. It inversely correlated with Unified Parkinson's Disease Rating Scale score. BChE activity decreased in PD-related dementia compared with those without dementia. The sensitivity and specificity values were 70.6% and 76.3%, respectively, with an optimal cut-off point of 6550.00 IU/L.

Conclusions

Serum BChE activity can be regarded as a biomarker for PD and related dementia.

Cerebrovascular risk factors for patients with cerebral watershed infarction: A case-control study based on computed tomography angiography in a population from Southwest China

To determine cerebrovascular risk factors for patients with cerebral watershed infarction (CWI) from Southwest China.Patients suffering from acute ischemic stroke were categorized into internal CWI (I-CWI), external CWI (E-CWI), or non-CWI (patients without CWI) groups. Clinical data were collected and degrees of steno-occlusion of all cerebral arteries were scored. Arteries associated with the circle of Willis were also assessed. Data were compared using Pearson chi-squared tests for categorical data and 1-way analysis of variance with Bonferroni post hoc tests for continuous data, as appropriate. Multivariate binary logistic regression analysis was performed to determine independent cerebrovascular risk factors for CWI.Compared with non-CWI, I-CWI had higher degrees of steno-occlusion of the ipsilateral middle cerebral artery, ipsilateral carotid artery, and contralateral middle cerebral artery. E-CWI showed no significant differences. All the 3 arteries were independent cerebrovascular risk factors for I-CWI confirmed by multivariate binary logistic regression analysis. I-CWI had higher degrees of steno-occlusion of the ipsilateral middle cerebral artery compared with E-CWI. No significant differences were found among arteries associated with the circle of Willis.The ipsilateral middle cerebral artery, carotid artery, and contralateral middle cerebral artery were independent cerebrovascular risk factors for I-CWI. No cerebrovascular risk factor was identified for E-CWI.

Recombinant Tissue Plasminogen Activator Induces Neurological Side Effects Independent on Thrombolysis in Mechanical Animal Models of Focal Cerebral Infarction: A Systematic Review and Meta-Analysis

BACKGROUND AND PURPOSE

Recombinant tissue plasminogen activator (rtPA) is the only effective drug approved by US FDA to treat ischemic stroke, and it contains pleiotropic effects besides thrombolysis. We performed a meta-analysis to clarify effect of tissue plasminogen activator (tPA) on cerebral infarction besides its thrombolysis property in mechanical animal stroke.

METHODS

Relevant studies were identified by two reviewers after searching online databases, including Pubmed, Embase, and ScienceDirect, from 1979 to 2016. We identified 6, 65, 17, 12, 16, 12 and 13 comparisons reporting effect of endogenous tPA on infarction volume and effects of rtPA on infarction volume, blood-brain barrier, brain edema, intracerebral hemorrhage, neurological function and mortality rate in all 47 included studies. Standardized mean differences for continuous measures and risk ratio for dichotomous measures were calculated to assess the effects of endogenous tPA and rtPA on cerebral infarction in animals. The quality of included studies was assessed using the Stroke Therapy Academic Industry Roundtable score. Subgroup analysis, meta-regression and sensitivity analysis were performed to explore sources of heterogeneity. Funnel plot, Trim and Fill method and Egger's test were obtained to detect publication bias.

RESULTS

We found that both endogenous tPA and rtPA had not enlarged infarction volume, or deteriorated neurological function. However, rtPA would disrupt blood-brain barrier, aggravate brain edema, induce intracerebral hemorrhage and increase mortality rate.

CONCLUSIONS

This meta-analysis reveals rtPA can lead to neurological side effects besides thrombolysis in mechanical animal stroke, which may account for clinical exacerbation for stroke patients that do not achieve vascular recanalization with rtPA.