Vascular injury biomarkers and stroke risk

Biomarkers for Early Detection of Stroke: A Systematic Review

Stroke remains a leading cause of mortality and disability worldwide. Identifying reliable biomarkers for stroke diagnosis and risk prediction could significantly improve patient outcomes through earlier intervention and better risk management. The objective of this systematic review is to systematically review recent studies investigating biomarkers for stroke diagnosis and risk prediction and to synthesize the most promising findings. We conducted a systematic review of 10 studies published between 2008 and 2023 that examined various biomarkers in relation to stroke. Studies were evaluated for quality using a simplified version of the Mixed Methods Appraisal Tool. The reviewed studies investigated a diverse array of biomarkers, including lipids, inflammatory markers, hemodynamic markers, microRNAs, metabolites, and neurodegenerative markers. Key findings include the following: (1) non-traditional lipid markers such as triglycerides and non-high-density lipoprotein cholesterol may be more predictive of stroke risk than low-density lipoprotein; (2) inflammatory markers, particularly IL-6, showed strong associations with stroke risk; (3) hemodynamic markers like midregional proatrial natriuretic peptide (MRproANP) and N-terminal pro-B-type natriuretic peptide (NT-proBNP) demonstrated potential in distinguishing stroke subtypes; (4) specific microRNAs (miR-125a-5p, miR-125b-5p, miR-143-3p) were upregulated in acute ischemic stroke; (5) metabolomic studies identified novel markers such as tetradecanedioate and hexadecanedioate associated with cardioembolic stroke; (6) neurodegenerative markers (total-tau, neurofilament light chain) were linked to increased stroke risk. This review highlights the potential of various biomarkers in improving stroke diagnosis and risk prediction. While individual markers show promise, a multi-marker approach combined with clinical variables appears most likely to yield clinically useful tools. Further large-scale validation studies are needed before these biomarkers can be implemented in routine clinical practice.

Fluid biomarkers of the neurovascular unit in cerebrovascular disease and vascular cognitive disorders: A systematic review and meta-analysis

Background

The disruption of the neurovascular unit (NVU), which maintains the integrity of the blood brain barrier (BBB), has been identified as a critical mechanism in the development of cerebrovascular and neurodegenerative disorders. However, the understanding of the pathophysiological mechanisms linking NVU dysfunction to the disorders is incomplete, and reliable blood biomarkers to measure NVU dysfunction are yet to be established. This systematic review and meta-analysis aimed to identify biomarkers associated with BBB dysfunction in large vessel disease, small vessel disease (SVD) and vascular cognitive disorders (VCD).

Methods

A literature search was conducted in PubMed, EMBASE, Scopus and PsychINFO to identify blood biomarkers related to dysfunction of the NVU in disorders with vascular pathologies published until 20 November 2023. Studies that assayed one or more specific markers in human serum or plasma were included. Quality of studies was assessed using the Newcastle-Ottawa Quality Assessment Scale. Effects were pooled and methodological heterogeneity examined using the random effects model.

Results

A total of 112 studies were included in this review. Where study numbers allowed, biomarkers were analysed using random effect meta-analysis for VCD (1 biomarker; 5 studies) and cerebrovascular disorders, including stroke and SVD (9 biomarkers; 29 studies) while all remaining biomarkers (n = 17 biomarkers; 78 studies) were examined through qualitative analysis. Results of the meta-analysis revealed that cerebrospinal fluid/serum albumin quotient (Q-Alb) reliably differentiates VCD patients from healthy controls (MD = 2.77; 95 % CI = 1.97-3.57; p < 0.0001) while commonly measured biomarkers of endothelial dysfunction (VEGF, VCAM-1, ICAM-1, vWF and E-selectin) and neuronal injury (NfL) were significantly elevated in vascular pathologies. A qualitative assessment of non-meta-analysed biomarkers revealed NSE, NfL, vWF, ICAM-1, VCAM-1, lipocalin-2, MMP-2 and MMP-9 levels to be upregulated in VCD, although these findings were not consistently replicated.

Conclusions

This review identifies several promising biomarkers of NVU dysfunction which require further validation. A panel of biomarkers representing multiple pathophysiological pathways may offer greater discriminative power in distinguishing possible disease mechanisms of VCD.

Value of novel thrombotic markers for predicting occurrence of the malignant cerebral artery infarction: a prospective clinical study

Objective

This study investigated the diagnostic performance of thrombin-antithrombin complex (TAT), plasmin-α2 plasmin inhibitor complex (PIC), tissue plasminogen activator-plasminogen activator inhibitor complex (t-PAIC), and thrombomodulin (TM) in predicting the progression of massive cerebral infarction to the malignant cerebral artery infarction.

Method

A total of 71 patients with massive cerebral infarction confirmed by imaging examination were divided into malignant cerebral artery infarction group (MCAI) and non-malignant cerebral artery infarction group (NMCAI) based on whether they progressed to MCAI after admission. TAT, PIC, t-PAIC, and TM were measured immediately after admission. The predictive performance was analyzed by the receiver characteristic operating curve (ROC).

Result

The median plasma concentrations of TM, PIC, TAT, and t-PAIC in the MCAI patients at admission were 10.65 IU/mL, 1.17 μg/mL, 12.25 ng/mL, and 13.85 ng/mL, respectively, which were higher than those in the NMCAI patients (9.00 IU/mL, 1.07 μg/mL, 4.60 ng/mL, and 8.70 ng/mL), and the difference was statistically significant (p = 0.045, p = 0.035, p = 0.004, and p = 0.003). Elevated plasma t-PAIC concentration was shown to be an independent risk factor for progression of massive cerebral infarction to MCAI (OR = 1.131) by multivariate logistic regression analysis. ROC curve analysis showed that t-PAIC was the best predictor of MCAI (AUC = 74.7%), with a sensitivity of 75.0% and specificity of 75.9% when t-PAIC concentration was ≥12.4 ng/mL; TAT had the highest specificity in predicting MCAI, with a specificity of 90.7% when the TAT concentration was ≥13.5 ng/mL.

Conclusion

The detection of PIC, TAT, t-PAIC, and TM is a comprehensive assessment of vascular endothelial damage and activation of the coagulation and fibrinolytic systems and has predictive value for poor prognosis in patients with MCAI. The widespread use of these tests will likely greatly improve the early diagnosis rate of MCAI.

Clinical study on the feasibility of new thrombus markers in predicting massive cerebral infarction

Objective

This study investigated the diagnostic performance of the thrombin-antithrombin complex (TAT), plasmin-α2 plasmin inhibitor complex (PIC), tissue plasminogen activator-plasminogen activator inhibitor complex (t-PAIC), and thrombomodulin (TM) in the early identification of massive cerebral infarction.

Method

A total of 423 patients with cerebral infarction confirmed by imaging examination were divided into the massive cerebral infarction (MCI) group and the non-massive cerebral infarction (NMCI) group. TAT, PIC, t-PAIC, and TM were measured immediately after admission. The diagnostic performance was analyzed by the receiver characteristic operating curve (ROC).

Result

The median plasma concentrations of TAT, PIC, and t-PAIC in patients with MCI at early onset were 5.10 ng/ml, 1.11 μg/ml, and 8.80 ng/ml, respectively, which were higher than those in patients with NMCI (2.20 ng/ml, 0.59 μg/ml, and 7.35 ng/ml), and the difference was statistically significant (P < 0.001). TAT was shown to be an independent risk factor for the development of massive cerebral infarction by a multivariate logistic regression analysis (OR = 1.138). A ROC curve analysis showed that PIC had the best performance in identifying MCI at an early stage (AUC = 82.8%), with a sensitivity of 80.7% and a specificity of 76.2% when the PIC concentration was ≥0.8 μg/ml; TAT had the highest specificity in identifying MCI, with a specificity of 80.6% when the TAT concentration was ≥3.97 ng/ml.

Conclusion

The detection of PIC, TAT, t-PAIC, and TM is a comprehensive assessment of vascular endothelial damage and activation of the coagulation and fibrinolytic systems and has diagnostic value for early identification of patients with MCI, which, together with its ease of detection, can be used as a plasma marker for early identification of large vessel occlusion.

Corneal nerve loss in patients with TIA and acute ischemic stroke in relation to circulating markers of inflammation and vascular integrity

Vascular and inflammatory mechanisms are implicated in the development of cerebrovascular disease and corneal nerve loss occurs in patients with transient ischemic attack (TIA) and acute ischemic stroke (AIS). We have assessed whether serum markers of inflammation and vascular integrity are associated with the severity of corneal nerve loss in patients with TIA and AIS. Corneal confocal microscopy (CCM) was performed to quantify corneal nerve fiber density (CNFD), corneal nerve branch density (CNBD) and corneal nerve fiber length (CNFL) in 105 patients with TIA (n = 24) or AIS (n = 81) and age matched control subjects (n = 56). Circulating levels of IL-6, MMP-2, MMP-9, E-Selectin, P-Selectin and VEGF were quantified in patients within 48 h of presentation with a TIA or AIS. CNFL (P = 0.000, P = 0.000), CNFD (P = 0.122, P = 0.000) and CNBD (P = 0.002, P = 0.000) were reduced in patients with TIA and AIS compared to controls, respectively with no difference between patients with AIS and TIA. The NIHSS Score (P = 0.000), IL-6 (P = 0.011) and E-Selectin (P = 0.032) were higher in patients with AIS compared to TIA with no difference in MMP-2 (P = 0.636), MMP-9 (P = 0.098), P-Selectin (P = 0.395) and VEGF (P = 0.831). CNFL (r = 0.218, P = 0.026) and CNFD (r = 0.230, P = 0.019) correlated with IL-6 and multiple regression analysis showed a positive association of CNFL and CNFD with IL-6 (P = 0.041, P = 0.043). Patients with TIA and AIS have evidence of corneal nerve loss and elevated IL6 and E-selectin levels. Larger longitudinal studies are required to determine the association between inflammatory and vascular markers and corneal nerve fiber loss in patients with cerebrovascular disease.

Association of Circulating ICAM3 Concentrations with Severity and Short-term Outcomes of Acute Ischemic Stroke

Increased circulating intercellular adhesion molecule 3 (ICAM3) is associated with a risk of acute ischemic stroke. This study aims to investigate the association of serum levels of ICAM3 with the severity and short-term outcomes of ischemic stroke. This study recruited 152 stroke patients with supratentorial cerebral infarcts and 133 healthy controls. Patients were followed up for 2 weeks since admission for observation of functional outcomes. Serum ICAM3 concentrations at baseline were determined by Elisa. Serum ICAM3 concentrations were higher in stroke patients than in healthy controls. Serum concentrations of ICAM3 were not associated with stroke severity at baseline, as reflected by NIH Stroke Scale (NIHSS) and infarction volume. However, serum ICAM3 levels were positively associated with mRS scores at 2 weeks since admission. Furthermore, regression analyses found that increased serum ICAM3 levels were associated with worse short-term functional outcomes of stroke. These findings imply that circulating ICAM3 might be a potential short-term prognostic biomarker for acute ischemic stroke.

Insights into therapeutic targets and biomarkers using integrated multi-'omics' approaches for dilated and ischemic cardiomyopathies

At present, heart failure (HF) treatment only targets the symptoms based on the left ventricle dysfunction severity; however, the lack of systemic 'omics' studies and available biological data to uncover the heterogeneous underlying mechanisms signifies the need to shift the analytical paradigm towards network-centric and data mining approaches. This study, for the first time, aimed to investigate how bulk and single cell RNA-sequencing as well as the proteomics analysis of the human heart tissue can be integrated to uncover HF-specific networks and potential therapeutic targets or biomarkers. We also aimed to address the issue of dealing with a limited number of samples and to show how appropriate statistical models, enrichment with other datasets as well as machine learning-guided analysis can aid in such cases. Furthermore, we elucidated specific gene expression profiles using transcriptomic and mined data from public databases. This was achieved using the two-step machine learning algorithm to predict the likelihood of the therapeutic target or biomarker tractability based on a novel scoring system, which has also been introduced in this study. The described methodology could be very useful for the target or biomarker selection and evaluation during the pre-clinical therapeutics development stage as well as disease progression monitoring. In addition, the present study sheds new light into the complex aetiology of HF, differentiating between subtle changes in dilated cardiomyopathies (DCs) and ischemic cardiomyopathies (ICs) on the single cell, proteome and whole transcriptome level, demonstrating that HF might be dependent on the involvement of not only the cardiomyocytes but also on other cell populations. Identified tissue remodelling and inflammatory processes can be beneficial when selecting targeted pharmacological management for DCs or ICs, respectively.