Editorial: Genetic Insights and Diagnostic Innovations in Cerebrovascular and Cerebrospinal Fluid Disorders

Ling Li^1*Haipeng Liu²Linfang Lan³Hao Yu⁴

• ¹Zhoushan Hospital, Zhoushan, China
• ²Coventry University, Coventry, United Kingdom
• ³The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
• ⁴The Second Affiliated Hospital Zhejiang University School of Medicine, Hangzhou, China

Genetics-centered precision neurology is reshaping both research and clinical practice in cerebrovascular disease and cerebrospinal fluid-related disorders. Technological advancements in multimodal neuroimaging, standardized laboratory testing, next-generation sequencing, transcriptomics, and extracellular-vesicle analytics are jointly accelerating the acquisition, management, processing, and interpretation of novel biomarkers towards clinical practice. The impact is evident in earlier etiologic clarification, finer-grained risk stratification, and biomarker-informed monitoring that spans the acute phase through rehabilitation. Within this Research Topic, Genetic Insights and Diagnostic Innovations in Cerebrovascular and Cerebrospinal Fluid Disorders, we assembled thirteen contributions—reviews, bioinformatics analyses, clinical cohort studies, neuroimaging investigations, and preclinical experimentation—that collectively illustrate how genetics and novel biomarkers are being applied to cerebrovascular and cerebrospinal fluid-related diseases (Table 1). Taken together, these studies provide up-to-date exemplars of how molecular insights can be translated into implementable diagnostic tools and mechanism-informed therapeutic strategies. Table 1. Summar of included studies. Theme Authors & DOI Study Title Key Findings Functional recovery biomarkers Mitra et al. (2025)[1] doi:10.3389/fneur.2025.1568401 Plasma cholinergic markers are associated with post-stroke walking recovery-revisiting the STROKEWALK study SMS-guided exercise improves 6MWT and limits BDNF decline, while cholinergic indices track walking gains and may serve as rehabilitation biomarkers. Hematologic marker HRR in older AIS Huang et al. (2025)[2] doi:10.3389/fneur.2025.1534564 Association between the hemoglobin-to-red cell distribution width ratio and three-month unfavorable outcome in older acute ischemic stroke patients: a prospective study A lower HRR was correlated with a higher risk for adverse outcome in older AIS patients. Hematologic ratios in AIS prognosis Li et al. (2025)[3] doi:10.3389/fneur.2025.1542889 Values of lymphocyte-related ratios in predicting the clinical outcome of acute ischemic stroke patients receiving intravenous thrombolysis based on different etiologies NLR predicts post thrombolysis outcomes across subtypes, especially in atherosclerotic stroke, supporting its use for risk stratification. Inflammatory index NPAR and stroke Ye et al. (2025)[4] doi:10.3389/fneur.2025.1520298 Cross-sectional study on the association between neutrophil-percentage-to-albumin ratio (NPAR) and prevalence of stroke among US adults: NHANES 1999-2018 Higher NPAR is independently associated with increased stroke prevalence. Metabolic stress in acute brain injury Wang et al. (2025)[5] doi:10.3389/fneur.2025.1552462 The stress hyperglycemia ratio as a predictor of short-and long-term mortality in patients with acute brain injury: a retrospective cohort study SHR independently predicts short-and long-term mortality in ABI and, with GCS and ventilation status, improves clinical risk stratification. Endocrine biomarker (Klotho) Xu et al. (2025)[6] doi:10.3389/fneur.2025.1573027 The association between serum klotho protein and stroke: a cross-sectional study from NHANES 2007-2016 Serum klotho showed an independent inverse association with stroke prevalence, consistent across most subgroups. Vascular genetics and geometry Wang et al. (2025)[7] doi:10.3389/fneur.2025.1498613 Association between Apolipoprotein E gene polymorphism and the tortuosity of extracranial carotid artery ApoE gene polymorphism are associated with the tortuosity of ECA,ε2 tended toward greater tortuosity, whereas ε4 appeared protective. Shared genomic signatures Wang et al. (2025)[8] doi:10.3389/fneur.2025.1567902 Exploration of the shared gene signatures and molecular mechanisms between cardioembolic stroke and ischemic stroke ABCA1, CLEC4E, and IRS2 were identified as potential key biomarkers and therapeutic targets for CS and IS. Imaging and perfusion in ICAS Xu et al. (2025)[9] doi:10.3389/fneur.2025.1551364 Associations of cerebral perfusion with infarct patterns and early neurological outcomes in symptomatic intracranial atherosclerotic stenosis Perfusion compromise aligned with border-zone and territorial infarcts, and greater penumbra-core mismatch (Tmax > 4 s) predicted early outcomes. Cellular therapy in stroke Wang et al. (2025)[10] doi:10.3389/fneur.2025.1583982 Oligodendrocyte precursor cell transplantation attenuates inflammation after ischemic stroke in mice Oligodendrocyte precursor cell transplantation reduces neuroinflammation and preserves the blood-brain barrier in AIS, supporting its therapeutic potential. Natural Yu et al. (2025)[11] Targeting microglia polarization Natural compounds compounds and microglia doi:10.3389/fcell.2025.1580479 with Chinese herb-derived natural compounds for neuroprotection in ischemic stroke that dampen microglia-mediated inflammation while promoting neuroprotective polarization represent a promising therapeutic strategy for IS. Blood biomarkers review Liang et al. (2025)[12] doi:10.3389/fneur.2025.1488726 Advances in the detection of biomarkers for ischemic stroke Surveyed blood biomarkers across diverse biological pathways and underscored challenges and clinical applicability. Bibliometric and research trends Ding et al. (2025)[13] doi:10.3389/fneur.2025.1595379 Knowledge mapping of exosomes in ischemic stroke: a bibliometric analysis The research hotpots revealed in knowledge mapping include the role of endogenous exosomes in initiating and progressing ischemic stroke, as well as the potential therapeutic applications of exogenous exosomes. Notes: SMS: short-message-service; 6MWT: six-minute walk test; BDNF: brain-derived neurotrophic factor; HRR: hemoglobin-to-red cell distribution width ratio; AIS: acute ischemic stroke; NLR: neutrophil-to-lymphocyte ratio; NPAR: neutrophil-percentage-to-albumin ratio; ABI: acute brain injury; GCS: Glasgow Coma Scale; ApoE: Apolipoprotein E; ECA: extracranial carotid artery; CS: cardioembolic stroke; ICAS: intracranial atherosclerotic stenosis; IS: ischemic stroke. We observed that multiple low-cost and readily obtainable blood biomarkers show promise for risk stratification and outcome prediction. Building on a randomized study, Mitra et al.[1] showed that short-message-service–guided exercise improved post-stroke six-minute walk test (6MWT) performance and attenuated the decline in brain-derived neurotrophic factor (BDNF). Changes in choline acetyltransferase (ChAT) activity and in the ChAT/butyrylcholinesterase (ChAT/BChE) index correlated with 6MWT outcomes, with stronger signals observed in women for ChAT activity. This synchronized acquisition of biomarker and behavioral endpoints highlights the potential of peripheral markers as tools for monitoring treatment response. In an observational analysis of 1,470 older adults with acute ischemic stroke (AIS), Huang et al.[2] identified a nonlinear inverse association between a lower hemoglobin-to–red cell distribution width ratio (HRR) and a higher risk of unfavorable three-month outcomes. The restricted cubic spline modeling indicated an optimal inflection at 10.70, with an area under the curve of approximately 0.64 . Lower HRR signaled greater risk. As a zero-additional-cost index derived from routine hematology, HRR may offer practical value for bedside risk stratification. In a cohort of AIS patients treated with intravenous thrombolysis, Li et al.[3] evaluated the etiology-dependent prognostic value of lymphocyte-related ratios. The neutrophil-to-lymphocyte ratio (NLR) consistently predicted 90-day outcomes across Trial of Org 10,172 in Acute Stroke Treatment (TOAST) subtypes with subtype-specific cutoffs and was associated with adverse outcomes in each category, whereas the lymphocyte-to-monocyte ratio (LMR) showed predictive value primarily in the large-artery atherosclerosis subtype. Using a large United States adult cohort and multivariable logistic regression, Ye et al. [4] examined the neutrophil percentage-to-albumin ratio (NPAR) in relation to stroke prevalence and found that higher NPAR was associated with higher prevalence. These findings provide new insight for primary prevention and support NPAR as a practical tool for estimating stroke likelihood. Drawing on a clinical database of critically ill patients with acute brain injury, Wang et al. [5] assessed the stress hyperglycemia ratio (SHR) and showed that it independently predicts both short-and long-term mortality. When combined with the Glasgow Coma Scale (GCS) and ventilation status, SHR further improved risk stratification, supporting its use as a practical and feasible quantitative metric in intensive care settings. In a large cross-sectional analysis of the National Health and Nutrition Examination Survey (NHANES), Xu et al.[6] used weighted multivariable models with stratified interaction testing and provided the first population-level evidence of an independent inverse association between serum klotho and stroke risk. The association was consistent across most subgroups. These results suggest that anti-aging endocrine pathways may modulate cerebrovascular risk, indicating the possibility of developing hormone biomarker panels for risk stratification. With respect to genetics and large-vessel structural phenotypes, Wang et al.[7] examined the association between apolipoprotein E (APOE) genotype and extracranial carotid artery (ECA) tortuosity in a Chinese cohort and found that the ε2 allele may be associated with the increased tortuosity of ECA, whereas the ε4 allele might be a protective factor. These observations suggest that lipid-metabolism genotypes may influence the geometry of cerebral arteries. Integrating peripheral-blood transcriptomes across multiple Gene Expression Omnibus cohorts, Wang et al.[8] further identified that ABCA1, CLEC4E, and IRS2 were potential key biomarkers and therapeutic targets for cardioembolic stroke and ischemic stroke, serving as shared feature genes. Their expression correlates closely with neutrophil infiltration and autophagy activation, and a nomogram based on these markers demonstrates potential clinical applicability. This progression from single-gene signals to systems-level networks suggests translatable diagnostic and therapeutic targets. In symptomatic intracranial atherosclerotic stenosis (sICAS), Xu et al.[9] linked cerebral perfusion patterns to infarct topography and early neurological outcomes. Specific perfusion abnormality profiles were associated with cortical and subcortical infarct distributions as well as short-term clinical trajectories, underscoring the central role of hemodynamic compromise in risk stratification of sICAS and identifying the candidates for intensified hemodynamic management. The penumbra-infarct core mismatch volume in CT perfusion, with Tmax of >4s defining the penumbra, was associated with early neurological outcomes of sICAS patients. On the translational front, using a murine transient middle cerebral artery occlusion model, Wang et al.[10] evaluated the anti-inflammatory and blood-brain barrier (BBB)–protective effects of oligodendrocyte precursor cell (OPC) transplantation. OPCs reduced neuroinflammation, preserved BBB integrity, decreased infarct volume, and improved neurobehavioral outcomes, with benefits associated with Wnt/β-catenin signaling. These findings indicate a promising therapeutic strategy for ischemic stroke. From a phytochemistry perspective, Yu et al.[11] reviewed natural compounds derived from traditional Chinese medicine (TCM) that regulate microglial polarization to achieve neuroprotection after ischemic stroke. Multiple classes of compounds inhibit pro-inflammatory polarization and/or promote protective polarization, thereby exerting neuroprotective effects within a multitarget network. The review systematically catalogues candidate molecules and pathways, summarizes delivery innovations, and emphasizes the need for standardized pharmacology, pharmacokinetics, and quality control towards standardized and personalized TCM treatment and management of ischemic stroke. Liang et al.[12] present a comprehensive synthesis of blood-based biomarkers in ischemic stroke, spanning coagulation and fibrinolysis pathways, endothelial dysfunction markers, inflammatory mediators, neuronal and axonal injury markers, and extracellular vesicles with their circular RNAs. The review also surveys contemporary detection platforms and assay methodologies, providing critical guidance for clinical implementation. Across these categories, many candidates show promise for etiologic subtyping, early neurological deterioration, and prognostic assessment, thereby bridging molecular mechanisms to deployable diagnostic assays. Using bibliometric methods, Ding et al[13]. comprehensively appraised exosome research in ischemic stroke, focusing on endogenous and therapeutic exosomes, engineered cargo, and delivery across the blood-brain barrier. This data-driven landscape provides valuable references and resources to guide further exploration of exosome-based diagnostics and therapeutics. This Research Topic delineates some research hotspots of genetics in cerebral circulation and relevant diseases. The collection spans bibliometric analysis and methodological reviews [12, 13]; low-cost hematologic ratios for risk stratification and prognosis [2-5]; endocrine and rehabilitation-related markers [1, 6]; genetic and molecular biomarkers [7, 8, 12, 13]; and perfusion-based imaging phenotypes linked to early clinical outcomes [9]. The cell-based and natural-product interventions establish a foundation for mechanism-guided therapies [10, 11]. These contributions also advance clinical decision support by integrating inexpensive hematologic indices with imaging and transcriptomic information, aiming to raise diagnostic precision towards acute management, etiologic classification, prognostic stratification, and rehabilitation follow-up. Notwithstanding this progress, several challenges remain: insufficient availability of high-quality specimens and multicenter external validation [1-7, 9], lack of standardization in pre-analytical workflows and analytical platforms [8, 12, 13], limited interpretability and portability of multimodal models [8, 13], constraints in clinical integration and turnaround time [12, 13], incomplete translational and regulatory pathways [10, 11], with ethics concerns on equity and accessibility [4, 6]. Figure 1 provides an overview of the selected contributions and maps current limitations and future research directions. In future research, priorities include establishing multicenter prospective cohorts and biobanks; refining standardized preprocessing and quality-control frameworks; and computational models based on multimodal big data. Current efforts could be coupled with advanced computational modeling—such as computational fluid dynamics (CFD), fluid-structure interaction (FSI), and multiphysics simulation—to reconstruct cerebral and cerebrospinal fluid dynamics [14-17]. Genomics and multi-omics can delineate risk loci and pathways for pathological analysis [18-21]. Furthermore, interpretable artificial intelligence (AI) approaches that integrate neuroimaging, biochemical, genetic, and hemodynamic features, as well as large-scale multimodal clinical data can improve diagnostic accuracy and prognostic performance [22-26]. In parallel, mechanism-anchored early-phase translation should be accelerated to support the development and evaluation of targeted interventions. Taken together, these computational and data-driven approaches will enable mechanistic elucidation, early diagnosis, and the optimization of intervention towards individualized therapy and precise medicine. Figure 1. Overview of this Special Issue. The top colored panels summarize the research topics represented by the selected contributions: (i) clinical biomarkers and imaging; (ii) genetic and molecular biomarkers; and (iii) translational interventions. The central hub depicts AI, modeling, and data science, which are also prioritized as future directions. The bottom outline panels synthesize the limitations of the current state of the art and the corresponding priorities for future research. Abbreviations and acronyms: AI, artificial intelligence; APOE, apolipoprotein E; CFD, computational fluid dynamics; ChAT, choline acetyltransferase; CTP, computed tomography perfusion; FSI, fluid–structure interaction; HRR, hemoglobin-to–red cell distribution width ratio; QC, quality control; NLR, neutrophil-to-lymphocyte ratio; NPAR, neutrophil percentage-to-albumin ratio; SHR, stress hyperglycemia ratio; sICAS, symptomatic intracranial atherosclerotic stenosis; OPC, oligodendrocyte precursor cell.