Circulating Non-coding RNAs as Potential Biomarkers for Ischemic Stroke: A Systematic Review

Diagnostic efficacy of long non-coding RNAs in multiple sclerosis: a systematic review and meta-analysis

Background

Currently, an increasing body of research suggests that blood-based long non-coding RNAs (lncRNAs) could serve as biomarkers for diagnosing multiple sclerosis (MS). This meta-analysis evaluates the diagnostic capabilities of selected lncRNAs in distinguishing individuals with MS from healthy controls and in differentiating between the relapsing and remitting phases of the disease.

Methods

We conducted comprehensive searches across seven databases in both Chinese and English to identify relevant studies, applying stringent inclusion and exclusion criteria. The quality of the selected references was rigorously assessed using the QUADAS-2 tool. The analysis involved calculating summarized sensitivity (SSEN), specificity (SSPE), positive likelihood ratio (SPLR), negative likelihood ratio (SNLR), and diagnostic odds ratio (DOR) with 95% confidence intervals (CIs). Accuracy was assessed using summary receiver operating characteristic (SROC) curves.

Results

Thirteen high-quality studies were selected for inclusion in the meta-analysis. Our meta-analysis assessed the combined diagnostic performance of lncRNAs in distinguishing MS patients from healthy controls. We found a SSEN of 0.81 (95% CI: 0.74-0.87), SSPE of 0.84 (95% CI: 0.78-0.89), SPLR of 5.14 (95% CI: 3.63-7.28), SNLR of 0.22 (95% CI: 0.16-0.31), and DOR of 23.17 (95% CI: 14.07-38.17), with an AUC of 0.90 (95% CI: 0.87-0.92). For differentiating between relapsing and remitting MS, the results showed a SSEN of 0.79 (95% CI: 0.71-0.85), SSPE of 0.76 (95% CI: 0.64-0.85), SPLR of 3.34 (95% CI: 2.09-5.33), SNLR of 0.28 (95% CI: 0.19-0.40), and DOR of 12.09 (95% CI: 5.70-25.68), with an AUC of 0.84 (95% CI: 0.81-0.87).

Conclusion

This analysis underscores the significant role of lncRNAs as biomarkers in MS diagnosis and differentiation between its relapsing and remitting forms.

Serum Olink Proteomics-Based Identification of Protein Biomarkers Associated with the Immune Response in Ischemic Stroke

The immune response is considered essential for pathology of ischemic stroke (IS), but it remains unclear which immune response-related proteins exhibit altered expression in IS patients. Here, we used Olink proteomics to examine the expression levels of 92 immune response-related proteins in the sera of IS patients (n = 88) and controls (n = 88), and we found that 59 of these proteins were differentially expressed. Feature variables were screened from the differentially expressed proteins by the least absolute shrinkage and selection operator (LASSO) and the random forest and by determining whether their proteins had an area under the curve (AUC) greater than 0.8. Ultimately, we identified six potential protein biomarkers of IS, namely, MASP1, STC1, HCLS1, CLEC4D, PTH1R, and PIK3AP1, and established a logistic regression model that used these proteins to diagnose IS. The AUCs of the models in the internal validation and the test set were 0.962 (95% confidence interval (CI): 0.895-1.000) and 0.954 (95% CI: 0.884-1.000), respectively, and the same protein detection method was performed in an external independent validation set (AUC: 0.857 (95% CI: 0.801-0.913)). These proteins may play a role in immune regulation via the C-type lectin receptor signaling pathway, the PI3K-AKT signaling pathway, and the B-cell receptor signaling pathway.

Non-coding RNAs versus protein biomarkers to diagnose and differentiate acute stroke: Systematic review and meta-analysis

BACKGROUND

Stroke diagnosis is dependent on lengthy clinical and neuroimaging assessments, while rapid treatment initiation improves clinical outcome. Currently, more sensitive biomarker assays of both non-coding RNA- and protein biomarkers have improved their detectability, which could accelerate stroke diagnosis. This systematic review and meta-analysis compares non-coding RNA- with protein biomarkers for their potential to diagnose and differentiate acute stroke (subtypes) in (pre-)hospital settings.

METHODS

We performed a systematic review and meta-analysis of studies evaluating diagnostic performance of non-coding RNA- and protein biomarkers to differentiate acute ischemic and hemorrhagic stroke, stroke mimics, and (healthy) controls. Quality appraisal of individual studies was assessed using the QUADAS-2 tool while the meta-analysis was performed with the sROC approach and by assessing pooled sensitivity and specificity, diagnostic odds ratios, positive- and negative likelihood ratios, and the Youden Index.

SUMMARY OF REVIEW

112 studies were included in the systematic review and 42 studies in the meta-analysis containing 11627 patients with ischemic strokes, 2110 patients with hemorrhagic strokes, 1393 patients with a stroke mimic, and 5548 healthy controls. Proteins (IL-6 and S100 calcium-binding protein B (S100B)) and microRNAs (miR-30a) have similar performance in ischemic stroke diagnosis. To differentiate between ischemic- or hemorrhagic strokes, glial fibrillary acidic protein (GFAP) levels and autoantibodies to the NR2 peptide (NR2aAb, a cleavage product of NMDA neuroreceptors) were best performing whereas no investigated protein or non-coding RNA biomarkers differentiated stroke from stroke mimics with high diagnostic potential.

CONCLUSIONS

Despite sampling time differences, circulating microRNAs (< 24 h) and proteins (< 4,5 h) perform equally well in ischemic stroke diagnosis. GFAP differentiates stroke subtypes, while a biomarker panel of GFAP and UCH-L1 improved the sensitivity and specificity of UCH-L1 alone to differentiate stroke.

Multi-Level Biomarkers for Early Diagnosis of Ischaemic Stroke: A Systematic Review and Meta-Analysis

Blood biomarkers hold potential for the early diagnosis of ischaemic stroke (IS). We aimed to evaluate the current weight of evidence and identify potential biomarkers and biological pathways for further investigation. We searched PubMed, EMBASE, the Cochrane Library and Web of Science, used R package meta4diag for diagnostic meta-analysis and applied Gene Ontology (GO) analysis to identify vital biological processes (BPs). Among 8544 studies, we included 182 articles with a total of 30,446 participants: 15675 IS, 2317 haemorrhagic stroke (HS), 1798 stroke mimics, 846 transient ischaemic attack and 9810 control subjects. There were 518 pooled biomarkers including 203 proteins, 114 genes, 108 metabolites and 88 transcripts. Our study generated two shortlists of biomarkers for future research: one with optimal diagnostic performance and another with low selection bias. Glial fibrillary acidic protein was eligible for diagnostic meta-analysis, with summary sensitivities and specificities for differentiating HS from IS between 3 h and 24 h after stroke onset ranging from 73% to 80% and 77% to 97%, respectively. GO analysis revealed the top five BPs associated with IS. This study provides a holistic view of early diagnostic biomarkers in IS. Two shortlists of biomarkers and five BPs warrant future investigation.

The autophagy in ischemic stroke: A regulatory role of non-coding-RNAs

Ischemic stroke (IS) is a central nervous system neurological disorder ascribed to an acute focal trauma, with high mortality and disability, leading to a heavy burden on family and society. Autophagy is a self-digesting process by which damaged organelles and useless proteins are recycled to maintain cellular homeostasis, and plays a pivotal role in the process of IS. Non-coding RNAs (ncRNAs), mainly contains microRNA, long non-coding RNA and circular RNA, have been extensively investigated on regulation of autophagy in human diseases. Recent studies have implied that ncRNAs-regulating autophagy participates in pathophysiological process of IS, including cell apoptosis, inflammation, oxidative stress, blood-brain barrier damage and glial activation, which indicates that regulating autophagy by ncRNAs may be beneficial for IS treatment. This review summarizes the role of autophagy in IS, as well as focuses on the role of ncRNAs-mediated autophagy in IS, for the development of potential therapeutic strategies in this disease.

Novel Biomarkers of Atherosclerotic Vascular Disease-Latest Insights in the Research Field

The atherosclerotic vascular disease is a cardiovascular continuum in which the main role is attributed to atherosclerosis, from its appearance to its associated complications. The increasing prevalence of cardiovascular risk factors, population ageing, and burden on both the economy and the healthcare system have led to the development of new diagnostic and therapeutic strategies in the field. The better understanding or discovery of new pathophysiological mechanisms and molecules modulating various signaling pathways involved in atherosclerosis have led to the development of potential new biomarkers, with key role in early, subclinical diagnosis. The evolution of technological processes in medicine has shifted the attention of researchers from the profiling of classical risk factors to the identification of new biomarkers such as midregional pro-adrenomedullin, midkine, stromelysin-2, pentraxin 3, inflammasomes, or endothelial cell-derived extracellular vesicles. These molecules are seen as future therapeutic targets associated with decreased morbidity and mortality through early diagnosis of atherosclerotic lesions and future research directions.