Biomarker Differences in Aneurysmal Subarachnoid Hemorrhage: A Comparative Study of Patients With and Without Delayed Cerebral Ischemia

Biomarker Differences in Aneurysmal Subarachnoid Hemorrhage: A Comparative Study of Patients With and Without Delayed Cerebral Ischemia | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Biomarker Differences in Aneurysmal Subarachnoid Hemorrhage: A Comparative Study of Patients With and Without Delayed Cerebral Ischemia Manel Santafé Colomina, Manuel Quintana, Anna Sánchez, Rosa-Maria Gràcia, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7203739/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 21 Nov, 2025 Read the published version in Neurocritical Care → Version 1 posted 5 You are reading this latest preprint version Abstract Background: Delayed cerebral ischemia (DCI) is a major cause of morbidity following aneurysmal subarachnoid hemorrhage (aSAH), yet early prediction remains challenging. This study aimed to identify blood-based protein biomarkers within 24 hours of ICU admission associated with DCI using high-throughput proteomics. Methods: We conducted a prospective longitudinal study including 86 aSAH patients, of whom 28 developed DCI. For this exploratory analysis, we matched 8 patients who developed DCI with 8 controls without DCI based on age, sex, and severity scores. Plasma samples were analyzed using the Olink® Explore 3072 platform targeting 2,943 proteins. Differential expression analysis was performed using linear Bayesian models with FDR correction. Results: We identified 15 significantly dysregulated proteins (p < 0.01) in DCI patients. Key downregulated proteins included THSD1, CA3, and PROK1—associated with vascular integrity and endothelial function. Upregulated proteins included BGN, IFNG, and CSF2—related to innate immunity and neuroinflammation. Novel candidates such as CLSTN3 and DOCK9 also showed altered expression. Protein-protein interaction and GO enrichment analyses revealed involvement in inflammatory, immune, and metabolic pathways. Conclusions: Our findings suggest a distinct early molecular signature in aSAH patients who develop DCI, characterized by pro-inflammatory and neurovascular dysfunction markers. These candidate biomarkers warrant further validation in larger cohorts and may guide early risk stratification and therapeutic interventions. Figures Figure 1 Figure 2 Figure 3 INTRODUCTION Spontaneous Subarachnoid Hemorrhage is a neurological disorder characterized by non-traumatic bleeding into the subarachnoid space. In 80% of cases, it is due to the rupture of an arterial aneurysm (aSAH). Up to 46% of aSAH survivors experience significant long-term cognitive impairment, which is associated with poorer functional status and quality of life 1-3 . aSAH can lead to multiple non-neurological complications, including stress-induced neurogenic cardiomyopathy, cardiogenic acute pulmonary edema, and acute respiratory distress syndrome 4-8 . Among the neurological complications, the development of delayed cerebral ischemia (DCI) remains a major cause of morbidity and is a key determinant of poor outcome 9 . Diagnosing these complications remains challenging, and their clinical course and prognosis are not yet fully understood. Blood-based biomarkers may help support diagnostic processes and offer prognostic insights, enabling individualized monitoring and treatment strategies. Post-aSAH inflammatory responses have been increasingly studied in recent years due to their potential role in potential complications. In this regard, several inflammatory markers have shown promising results, and research studies have already suggested that inflammation could contribute to the pathophysiology of DCI 10,11 . Recent animal studies have demonstrated a link between systemic inflammation and acute brain injury 12,13 and other studies in humans have suggested a possible relationship between inflammatory activity in cerebrospinal fluid and clinical outcomes in aSAH patients 14 . However, further research is needed to clarify the mechanisms involved in DCI development after aSAH and their potential therapeutic implications. In this context, identifying biomarkers may help to differentiate inflammatory from non-inflammatory mechanisms involved in DCI. To further investigate the pathophysiological mechanisms underlying DCI in aSAH, this study aims to identify potential inflammatory blood biomarkers associated with DCI and assess their relevance in predicting clinical outcomes. As part of an exploratory proteomic approach, the study is also intended to generate hypotheses for future research and validation in larger, independent cohorts. METHODS Study Cohort We conducted a prospective longitudinal study in a cohort of patients diagnosed with aSAH admitted into the Intensive Care Unit of our Hospital Center from July 2017 to June 2020 (see Figure 1 ). Blood samples were collected within the first 24 hours of ICU admission. Clinical variables include demographic, risk factors, laboratory and clinical variables listed in Table 1 The study cohort was divided in those patients who developed DCI (SAH-DCI) and those who did not (SAH-control), allowing for a comparative analysis of biomarker expression between groups. DCI was defined as the appearance of focal neurological deterioration or a decrease in consciousness by two or more points on the Glasgow Coma Scale (GCS) for at least one hour, which was not present immediately after aneurysm occlusion and cannot be attributed to other causes such as rebleeding or hydrocephalus 15 . For the present discovery study, eight patients with SAH-DCI randomly selected from the whole cohort and matched SAH-controls (without DCI) based on age, sex, and initial severity characteristics based in GCS, Fisher and WFNS scores. Biomarker Discovery Plasma samples, previously collected into Vacutainer® tubes containing EDTA (Becton Dickinson, Franklin Lakes, NJ, USA) and centrifuged at 1,500 × g for 15 minutes at 4 °C, were aliquoted and stored at −80 °C until analysis. These samples were externally characterized by Olink Proteomics® (Uppsala, Sweden) using the Olink® Explore 3072 library, which consists of eight disease- and biological process-focused 384-plex panels. These panels target proteins related to cardiovascular and metabolic diseases, immunological and inflammatory conditions, neurological and neurobiological disorders, and the fields of oncology and immuno-oncology. A biomarker discovery analysis was conducted on samples from 8 SAH-DCI patients and 8 SAH-control patients. In all cases, blood samples were collected in EDTA tubes and centrifuged at 1500 x g for 15 minutes at 4°C to obtain plasma fractions which were stored frozen in aliquots at −80°C until use. A biomarker discovery analysis was conducted using Olink® Proximity Extension Assay (PEA) technology (Olink Proteomics, Uppsala, Sweden) to measure plasma levels of 2,943 proteins across eight 96-protein panels —including neurology, oncology, inflammation, cardiovascular, and cardiometabolic pathways— in samples from SAH-DCI and SAH-control patients.The mentioned technology enables a high-throughput, multiplex immunoassay of each panel using 1 μL of plasma in a 96-well-plate. Statistical analysis Data analysis was carried out with R software (version 4.2.1; R Foundation for Statistical Computing, Vienna, Austria) and the IBM SPSS statistical package (version 25; SPSS Inc., Armonk, NY, USA). To analyze data generated by the Olink Proteomics assays, proteins with more than 30% of values below the detection limit were not considered for further analysis. Thereafter, differential expression analysis (SAH-DCI vs. SAH-controls) was carried out using linear Bayes models in the limma Bioconductor package 16 . The false discovery rate (FDR) was applied for correction in multiple comparisons, and the log fold change (logFC) was used to analyze the magnitude of the differences. Differentially-expressed proteins were screened out using volcano plots. A heatmap was drawn to visualize the proteins exhibiting the most significant differences in expression levels between groups. Protein interactions analysis To evaluate and visualize interactions between identified proteins showing statistical significance (p<0.05) in the discovery analysis, we used the STRING database (version 12.0) to identify known and predicted protein-protein interactions. The interactions include direct (physical) and indirect (functional) associations; they stem from computational prediction, from knowledge transfer between organisms, and from interactions aggregated from other (primary) databases (https://string-db.org/). GO ontology analysis A biological significance analysis was performed; for this purpose, the proteins identified as validated targets were first mapped to their corresponding coding genes. These gene identifiers were then uploaded to Enrich (gene set enrichment analysis web server) to explore associated gene ontology biological processes, molecular functions, and pathway involvement. P-values < 0.05 were considered statistically significant. RESULTS Demographic and Clinical Characteristics A baseline sample was obtained from a total of 86 patients with a confirmed diagnosis of aSAH, with a mean age of 58.6 ± 12.3, 24 (27.9%) male and 62 (72.1%) female. 28 patients (32.6%) developed delayed cerebral ischemia (DCI). 11 in-hospital deaths of the non-DCI group were excluded for the discovery analysis (Fig. 1). Finally, we randomly selected 8 patients who developed DCI (SAH-DCI) and were matched with 8 patients who did not (SAH-controls) with similar characteristics, for a total of 16 aSAH patients included in the biomarker discovery analysis. 62.5% subjects of each group were females (p = 1.000) and the mean age was comparable between groups (56.9 ± 12.9 vs 57.0 ± 11.5 years; p = 0.986), as well as other risk factors and clinical characteristics ( Table 1 ). Differential protein expression in blood as potential biomarkers of DCI. Among the eleven proteins (Fig. 2) showing the lowest expression levels in SAH-DCI patients compared to SAH-controls (p < 0.01), only CA3, PROK1, THSD1, and MYL4 belonged to the neuroinflammatory biomarker panel, whereas the remaining proteins (CEACAM19, AMY2B, AMY2A, AHSP, SPINK6, PNLIPRP2 and CENPF) belong to the oncologic biomarker panel. On the other hand, IFNG, DOCK 9, CLSTN3, XCL1, BGN and CSF2 were found overexpressed in SAH-DCI patients compared to SAH-controls (p < 0.01 ) . A complete table of the differential expression of proteins between SAH-DCI and SAH-control patients can be found in Table 2 . Protein interaction analysis The protein-protein interaction (PPI) network analysis revealed connectivity among the identified biomarkers, suggesting that these proteins may participate in diverse biological pathways. The strongest interaction was observed between AMY2A and AMY2B, likely due to their high sequence similarity and shared enzymatic function (Fig. 3). DISCUSSION This prospective exploratory study provides new insights into the molecular mechanisms underlying DCI following aneurysmal subarachnoid hemorrhage (aSAH). Through high-throughput proteomic analysis, we identified several differentially expressed proteins within 24 hours of ICU admission, being early alterations in inflammatory and neurodegenerative biomarkers that could be associated with DCI development. Downregulated proteins Among the most significantly downregulated proteins in DCI patients were THSD1 (thrombospondin type 1 domain containing 1), CA3(carbonic anhydrase III), and PROK1 (prokineticin-1), all of which are involved in vascular function. THSD1 was of particular interest as it has been implicated in endothelial integrity and the formation of intracranial aneurysm 17,18 . Mutations in THSD1 have been shown to disrupt endothelial cell–extracellular matrix interactions, increasing vulnerability to aneurysmal rupture 18 . Although its role in DCI is less well established, its decreased expression may reflect ongoing endothelial instability or compromised blood-brain barrier function following hemorrhage. CA3 has been associated with vascular tone regulation 19 and its downregulation may suggest impaired acid-base regulation in the ischemic event. And PROK1, a known angiogenic factor, affects BBB permeability and endothelial function 20 , and its downregulation may reflect altered neovascular responses post-SAH. These findings highlight potential early endothelial dysfunction and compromised neurovascular resilience in DCI patients. Upregulated proteins Conversely, several proteins were significantly upregulated in DCI patients, suggesting a shift toward pro-inflammatory and cell death pathways. BGN (biglycan) acts as a damage-associated molecular pattern (DAMP) molecule, interacting with Toll-like receptors (TLRs) and initiating pro-inflammatory cascades, including NLRP3 inflammasome activation and caspase-1 mediated cytokine release 13,21 . Its overexpression supports a role for innate immunity and neuroinflammation in DCI development. Additionally, BGN’s involvement in fructose metabolism may reflect broader metabolic dysregulation in these patients. IFNG (Interferon-gamma) and CSF2 (GM-CSF) are two potent pro-inflammatory cytokines found elevated in the DCI group. IFNG is secreted by T-cells and NK cells and is known to induce apoptosis and enhance immune activation via the IFNGR pathway 22 . CSF2 (GM-CSF) might promote arteriogenesis and neuroprotection after ischemic stroke 23 , however it also modulates macrophage and neutrophil activity and enhances pro-inflammatory cytokine release 24 . Both cytokines may thus contribute to immune dysregulation, exacerbated inflammation and neuronal damage in DCI. These results underscore a robust pro-inflammatory signature that emerges within the first 24 hours in patients developing DCI. Novel and underexplored markers: Our study also identified less-characterized proteins that may represent novel contributors to DCI: DOCK9, a member of the "Dedicator of Cytokinesis" family, is poorly characterized in CNS disease and neuroinflammation. While DOCK10 has been implicated in central nervous system immune signaling 25 , the significance of DOCK9 requires further investigation, and its expression may reflect broader dysregulation l or signaling changes in immune-active cells. CLSTN3, also upregulated in DCI patients, has been recently associated with ferroptosis and iron metabolism, as part of the circAFF2–CLSTN3–miR-488 axis. It is implicated in neuronal death by downregulating miR-488, and it has been linked to ischemic stroke outcomes 26 . Its upregulation in DCI patients may reflect a susceptibility to iron-dependent cell death mechanisms triggered by hemoglobin breakdown and oxidative stress in the subarachnoid space and supporting a mechanistic link between hemorrhage burden and ischemic injury. Other novel upregulated biomarker is XCL1, a chemokine ligand implicated in traumatic brain injury (TBI). In TBI models, XCL1 expression increases early peaking at 24 hours and contributing to secondary injury mechanisms 27 . Its elevation in DCI may reflect a similar neuroinflammatory damage following aSAH. Functional Network Insights STRING-Cytoscape analysis revealed that several of the differentially expressed proteins, including MYL4, XCL1, CSF2, AHSP, and AMY2A/B function as central hub proteins with high interaction scores . This supports the concept of coordinated dysregulation rather than isolated marker elevation, and suggests that systemic stress responses (e.g., hemoglobin metabolism, inflammation, immune cell activation) converge early in patients predisposed to DCI 28 . Limitations and Future Directions Limitations of this study include the small sample size without external validation, which restricts statistical power and generalizability. This analysis should be considered exploratory and hypothesis-generating. Moreover, we did not integrate cerebrospinal fluid (CSF) analyses, which could provide more localized inflammatory insights. Finally, longitudinal follow-up is needed to assess the predictive value of these proteins over time. Nonetheless, our findings provide a valuable foundation for future biomarker-driven studies. The observed dysregulation in both classical (e.g., CSF2, BGN, XCL1) and novel (e.g., CLSTN3, MYL4) proteins supports the hypothesis that DCI arises from a complex interplay between endothelial dysfunction, neuroinflammation, and metabolic failure. Conclusion Our exploratory proteomic analysis identified a distinct set of differentially expressed proteins in aSAH patients who developed delayed cerebral ischemia (DCI) compared to those who did not. Among the identified biomarkers, BGN (a DAMP molecule linked to neuroinflammation), CSF2 (a key pro-inflammatory cytokine), and CLSTN3 (a novel protein potentially associated with ferroptosis and neuronal injury) emerged as the most promising candidates for further validation. Future studies in larger, multicenter cohorts are needed to validate their diagnostic and prognostic utility and to assess their potential for guiding early therapeutic interventions in patients at risk of DCI. Declarations Compliance with Journal Guidelines We confirm that this manuscript complies with all instructions to authors as outlined by Neurocritical Care. Author Contributions Manel Santafé, MD: Study conception and design, drafting and writing of the manuscript, interpretation of results, discussion and conclusions. Estevo Santamarina, MD, PhD: Conceptualization, study supervision, writing of the manuscript, interpretation of results, discussion and conclusions Manuel Quintana, PhD: Statistical analysis, methodological input, and study design discussions. Anna Penalba, PhD: Proteomic sample processing, biomarker analysis, manuscript revision. Anna Rosell, PhD : Supervision of proteomic analysis, data interpretation, manuscript revision. Laura Abraira, MD, PhD: Manuscript review and editing. Daniel Campos-Fernandez, MD, PhD: Manuscript review and editing. Anna Sánchez, MD: Manuscript review and editing. Rosa-Maria Gràcia, MD, PhD: Manuscript review and editing. Authorship Confirmation We confirm that all authors meet the criteria for authorship in accordance with ICMJE recommendations, and all have approved the final version of the manuscript. Originality Statement We confirm that this manuscript has not been published elsewhere and is not currently under consideration by another journal. Ethical Approval and Informed Consent This study was approved by the Institutional Review Board (IRB) of Hospital Universitari Vall d’Hebron (IRB: PR(AG)212/2017). All procedures were conducted in accordance with ethical standards, and written informed consent was obtained from all participants or their legal surrogates. For this prospective study, IRB approval was obtained prior to sample and data analysis. Conflict of Interest Disclosure The authors declare no conflicts of interest relevant to this work. Reporting Checklist This study follows the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) guidelines. All relevant items have been addressed in the manuscript. Funding This study was supported by a research grant from the Fundación Eugenio Rodríguez Pascual (FERP-2022-1) and constitutes a project derived from that funded research. The grant specifically covered the costs related to the biomarker analysis References Hoh BL, Ko NU, Amin-Hanjani S, et al. 2023 Guideline for the Management of Patients With Aneurysmal Subarachnoid Hemorrhage: A Guideline From the American Heart Association/American Stroke Association. Stroke 2023;54:e314-e70. Treggiari MM, Rabinstein AA, Busl KM, et al. Guidelines for the Neurocritical Care Management of Aneurysmal Subarachnoid Hemorrhage. Neurocritical care 2023;39:1-28. Mayer SA, Kreiter KT, Copeland D, et al. Global and domain-specific cognitive impairment and outcome after subarachnoid hemorrhage. Neurology 2002;59:1750-8. Zaroff JG, Leong J, Kim H, et al. Cardiovascular predictors of long-term outcomes after non-traumatic subarachnoid hemorrhage. 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Ciechanowska A, Popiolek-Barczyk K, Ciapała K, et al. Traumatic brain injury in mice induces changes in the expression of the XCL1/XCR1 and XCL1/ITGA9 axes. Pharmacological reports : PR 2020;72:1579-92. Mollan TL, Yu X, Weiss MJ, Olson JS. The role of alpha-hemoglobin stabilizing protein in redox chemistry, denaturation, and hemoglobin assembly. Antioxidants & redox signaling 2010;12:219-31. Tables Tables 1 to 2 are available in the Supplementary Files section Supplementary Files Table1.jpg Table 1: Clinical characteristics Table2..jpg Table 2. Differential expression of proteins between SAH-DCI and SAH-contro STROBEchecklistv4combined.pdf Cite Share Download PDF Status: Published Journal Publication published 21 Nov, 2025 Read the published version in Neurocritical Care → Version 1 posted Reviewers agreed at journal 28 Jul, 2025 Reviewers invited by journal 28 Jul, 2025 Editor invited by journal 28 Jul, 2025 Editor assigned by journal 25 Jul, 2025 First submitted to journal 24 Jul, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7203739","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":492084393,"identity":"eecb5b51-a4ca-4bf3-81b2-7502475a819f","order_by":0,"name":"Manel Santafé 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3","display":"","copyAsset":false,"role":"figure","size":59930,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend.\u003c/p\u003e","description":"","filename":"Figure3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7203739/v1/b2c4f7337d2b7c88a4c09ded.jpg"},{"id":96650197,"identity":"ddfdd445-175d-492d-8e5d-4f6576693878","added_by":"auto","created_at":"2025-11-24 16:09:36","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":921396,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7203739/v1/c2c3fc17-4795-4ec8-b9c5-8effd98ee516.pdf"},{"id":87906511,"identity":"5be80262-3b8c-4202-937a-d1855300a466","added_by":"auto","created_at":"2025-07-30 09:00:23","extension":"jpg","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":134913,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTable 1: \u003c/strong\u003eClinical characteristics\u003c/p\u003e","description":"","filename":"Table1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7203739/v1/a962b8c51a34893053ed932a.jpg"},{"id":87905195,"identity":"6b3cf9ba-a03b-4c9a-9fc2-cf8c1f180947","added_by":"auto","created_at":"2025-07-30 08:44:23","extension":"jpg","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":101660,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTable 2.\u003c/strong\u003e Differential expression of proteins between SAH-DCI and SAH-contro\u003c/p\u003e","description":"","filename":"Table2..jpg","url":"https://assets-eu.researchsquare.com/files/rs-7203739/v1/225760b63a2c05851371b593.jpg"},{"id":87905192,"identity":"5105daad-97d2-4a2f-8d0e-0af7fdb08dd8","added_by":"auto","created_at":"2025-07-30 08:44:23","extension":"pdf","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":19826,"visible":true,"origin":"","legend":"","description":"","filename":"STROBEchecklistv4combined.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7203739/v1/7bf95e5769247b7424bfb4b5.pdf"}],"financialInterests":"","formattedTitle":"Biomarker Differences in Aneurysmal Subarachnoid Hemorrhage: A Comparative Study of Patients With and Without Delayed Cerebral Ischemia","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eSpontaneous Subarachnoid Hemorrhage is a neurological disorder characterized by non-traumatic bleeding into the subarachnoid space. In 80% of cases, it is due to the rupture of an arterial aneurysm (aSAH). Up to 46% of aSAH survivors experience significant long-term cognitive impairment, which is associated with poorer functional status and quality of life \u003csup\u003e1-3\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eaSAH can lead to multiple non-neurological complications, including stress-induced neurogenic cardiomyopathy, cardiogenic acute pulmonary edema, and acute respiratory distress syndrome \u003csup\u003e4-8\u003c/sup\u003e. Among the neurological complications, the development of delayed cerebral ischemia (DCI) remains a major cause of morbidity and is a key determinant of poor outcome \u003csup\u003e9\u003c/sup\u003e. Diagnosing these complications remains challenging, and their clinical course and prognosis are not yet fully understood. Blood-based biomarkers may help support diagnostic processes and offer prognostic insights, enabling individualized monitoring and treatment strategies.\u003c/p\u003e\n\u003cp\u003ePost-aSAH inflammatory responses have been increasingly studied in recent years due to their potential role in potential complications. In this regard, several inflammatory markers have shown promising results, and research studies have already suggested that inflammation could contribute to the pathophysiology of DCI \u003csup\u003e10,11\u003c/sup\u003e. Recent animal studies have demonstrated a link between systemic inflammation and acute brain injury \u003csup\u003e12,13\u003c/sup\u003e and other studies in humans have suggested a possible relationship between inflammatory activity in cerebrospinal fluid and clinical outcomes in aSAH patients \u003csup\u003e14\u003c/sup\u003e. However, further research is needed to clarify the mechanisms involved in DCI development after aSAH and their potential therapeutic implications. In this context, identifying biomarkers may help to differentiate inflammatory from non-inflammatory mechanisms involved in DCI.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTo further investigate the pathophysiological mechanisms underlying DCI in aSAH, this study aims to identify potential inflammatory blood biomarkers associated with DCI and assess their relevance in predicting clinical outcomes. As part of an exploratory proteomic approach, the study is also intended to generate hypotheses for future research and validation in larger, independent cohorts.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cp\u003e\u003cstrong\u003eStudy Cohort\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe conducted a prospective longitudinal study in a cohort of patients diagnosed with aSAH admitted into the Intensive Care Unit of our Hospital Center from July 2017 to June 2020 (see \u003cstrong\u003eFigure 1\u003c/strong\u003e). Blood samples were collected within the first 24 hours of ICU admission. Clinical variables include demographic, risk factors, laboratory and clinical variables listed in \u003cstrong\u003eTable 1\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe study cohort was divided in those patients who developed DCI (SAH-DCI) and those who did not (SAH-control), allowing for a comparative analysis of biomarker expression between groups. DCI was defined as the appearance of focal neurological deterioration or a decrease in consciousness by two or more points on the Glasgow Coma Scale (GCS) for at least one hour, which was not present immediately after aneurysm occlusion and cannot be attributed to other causes such as rebleeding or hydrocephalus\u003csup\u003e15\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFor the present discovery study, eight patients with SAH-DCI randomly selected from the whole cohort and matched SAH-controls (without DCI) based on age, sex, and initial severity characteristics based in GCS, Fisher and WFNS scores.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBiomarker Discovery\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePlasma samples, previously collected into Vacutainer\u0026reg; tubes containing EDTA (Becton Dickinson, Franklin Lakes, NJ, USA) and centrifuged at 1,500 \u0026times; g for 15 minutes at 4 \u0026deg;C, were aliquoted and stored at \u0026minus;80 \u0026deg;C until analysis. These samples were externally characterized by Olink Proteomics\u0026reg; (Uppsala, Sweden) using the Olink\u0026reg; Explore 3072 library, which consists of eight disease- and biological process-focused 384-plex panels. These panels target proteins related to cardiovascular and metabolic diseases, immunological and inflammatory conditions, neurological and neurobiological disorders, and the fields of oncology and immuno-oncology.\u003c/p\u003e\n\u003cp\u003eA biomarker discovery analysis was conducted on samples from 8 SAH-DCI patients and 8 SAH-control patients.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn all cases, blood samples were collected in EDTA tubes and centrifuged at 1500 x g for 15 minutes at 4\u0026deg;C to obtain plasma fractions which were stored frozen in aliquots at \u0026minus;80\u0026deg;C until use.\u003c/p\u003e\n\u003cp\u003eA biomarker discovery analysis was conducted using Olink\u0026reg; Proximity Extension Assay (PEA) technology (Olink Proteomics, Uppsala, Sweden) to measure plasma levels of 2,943 proteins across eight 96-protein panels \u0026mdash;including neurology, oncology, inflammation, cardiovascular, and cardiometabolic pathways\u0026mdash; in samples from SAH-DCI and SAH-control patients.The mentioned technology enables a high-throughput, multiplex immunoassay of each panel using 1 \u0026mu;L of plasma in a 96-well-plate.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData analysis was carried out with R software (version 4.2.1; R Foundation for Statistical Computing, Vienna, Austria) and the IBM SPSS statistical package (version 25; SPSS Inc., Armonk, NY, USA).\u003c/p\u003e\n\u003cp\u003eTo analyze data generated by the Olink Proteomics assays, proteins with more than 30% of values below the detection limit were not considered for further analysis. Thereafter, differential expression analysis (SAH-DCI \u003cem\u003evs.\u003c/em\u003e SAH-controls) was carried out using linear Bayes models in the limma Bioconductor package \u003csup\u003e16\u003c/sup\u003e. The false discovery rate (FDR) was applied for correction in multiple comparisons, and the log fold change (logFC) was used to analyze the magnitude of the differences. Differentially-expressed proteins were screened out using volcano plots. A heatmap was drawn to visualize the proteins exhibiting the most significant differences in expression levels between groups.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eProtein interactions analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo evaluate and visualize interactions between identified proteins showing statistical significance (p\u0026lt;0.05) in the discovery analysis, we used the STRING database (version 12.0) to identify known and predicted protein-protein interactions. The interactions include direct (physical) and indirect (functional) associations; they stem from computational prediction, from knowledge transfer between organisms, and from interactions aggregated from other (primary) databases (https://string-db.org/).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGO ontology analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA biological significance analysis was performed; for this purpose, the proteins identified as validated targets were first mapped to their corresponding coding genes. These gene identifiers were then uploaded to Enrich (gene set enrichment analysis web server) to explore associated gene ontology biological processes, molecular functions, and pathway involvement. P-values \u0026lt; 0.05 were considered statistically significant.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003e\u003cb\u003eDemographic and Clinical Characteristics\u003c/b\u003e\u003c/p\u003e\u003cp\u003eA baseline sample was obtained from a total of 86 patients with a confirmed diagnosis of aSAH, with a mean age of 58.6\u0026thinsp;\u0026plusmn;\u0026thinsp;12.3, 24 (27.9%) male and 62 (72.1%) female. 28 patients (32.6%) developed delayed cerebral ischemia (DCI). 11 in-hospital deaths of the non-DCI group were excluded for the discovery analysis (Fig.\u0026nbsp;1). Finally, we randomly selected 8 patients who developed DCI (SAH-DCI) and were matched with 8 patients who did not (SAH-controls) with similar characteristics, for a total of 16 aSAH patients included in the biomarker discovery analysis. 62.5% subjects of each group were females (p\u0026thinsp;=\u0026thinsp;1.000) and the mean age was comparable between groups (56.9\u0026thinsp;\u0026plusmn;\u0026thinsp;12.9 vs 57.0\u0026thinsp;\u0026plusmn;\u0026thinsp;11.5 years; p\u0026thinsp;=\u0026thinsp;0.986), as well as other risk factors and clinical characteristics (\u003cb\u003eTable\u0026nbsp;1\u003c/b\u003e).\u003c/p\u003e\u003cp\u003e\u003cb\u003eDifferential protein expression in blood as potential biomarkers of DCI.\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAmong the eleven proteins (Fig.\u0026nbsp;2) showing the lowest expression levels in SAH-DCI patients compared to SAH-controls (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), only CA3, PROK1, THSD1, and MYL4 belonged to the neuroinflammatory biomarker panel, whereas the remaining proteins (CEACAM19, AMY2B, AMY2A, AHSP, SPINK6, PNLIPRP2 and CENPF) belong to the oncologic biomarker panel. On the other hand, IFNG, DOCK 9, CLSTN3, XCL1, BGN and CSF2 were found overexpressed in SAH-DCI patients compared to SAH-controls (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01\u003cb\u003e)\u003c/b\u003e.\u003c/p\u003e\u003cp\u003eA complete table of the differential expression of proteins between SAH-DCI and SAH-control patients can be found in \u003cb\u003eTable\u0026nbsp;2\u003c/b\u003e.\u003c/p\u003e\u003cp\u003e\u003cb\u003eProtein interaction analysis\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe protein-protein interaction (PPI) network analysis revealed connectivity among the identified biomarkers, suggesting that these proteins may participate in diverse biological pathways. The strongest interaction was observed between AMY2A and AMY2B, likely due to their high sequence similarity and shared enzymatic function (Fig.\u0026nbsp;3).\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThis prospective exploratory study provides new insights into the molecular mechanisms underlying DCI following aneurysmal subarachnoid hemorrhage (aSAH). Through high-throughput proteomic analysis, we identified several differentially expressed proteins within 24 hours of ICU admission, being early alterations in inflammatory and neurodegenerative biomarkers that could be associated with DCI development.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eDownregulated proteins\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eAmong the most significantly downregulated proteins in DCI patients were THSD1 (thrombospondin type 1 domain containing 1), CA3(carbonic anhydrase III), and PROK1 (prokineticin-1), all of which are involved in vascular function. THSD1 was of particular interest as it has been implicated in endothelial integrity and the formation of intracranial aneurysm \u003csup\u003e17,18\u003c/sup\u003e. Mutations in THSD1 have been shown to disrupt endothelial cell\u0026ndash;extracellular matrix interactions, increasing vulnerability to aneurysmal rupture \u003csup\u003e18\u003c/sup\u003e. Although its role in DCI is less well established, its decreased expression may reflect ongoing endothelial instability or compromised blood-brain barrier function following hemorrhage.\u003c/p\u003e\n\u003cp\u003eCA3 has been associated with vascular tone regulation \u003csup\u003e19\u003c/sup\u003e and its downregulation may suggest impaired acid-base regulation in the ischemic event. And PROK1, a known angiogenic factor, affects BBB permeability and endothelial function\u003csup\u003e20\u003c/sup\u003e, and its downregulation may reflect altered neovascular responses post-SAH.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThese findings highlight potential early endothelial dysfunction and compromised neurovascular resilience in DCI patients.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eUpregulated proteins\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eConversely, several proteins were significantly upregulated in DCI patients, suggesting a shift toward pro-inflammatory and cell death pathways.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eBGN (biglycan) acts as a damage-associated molecular pattern (DAMP) molecule, interacting with Toll-like receptors (TLRs) and initiating pro-inflammatory cascades, including NLRP3 inflammasome activation and caspase-1 mediated cytokine release \u003csup\u003e13,21\u003c/sup\u003e. Its overexpression supports a role for innate immunity and neuroinflammation in DCI development. Additionally, BGN\u0026rsquo;s involvement in fructose metabolism may reflect broader metabolic dysregulation in these patients.\u003c/p\u003e\n\u003cp\u003eIFNG (Interferon-gamma) and CSF2 (GM-CSF) are two potent pro-inflammatory cytokines found elevated in the DCI group. IFNG is secreted by T-cells and NK cells and is known to induce apoptosis and enhance immune activation via the IFNGR pathway \u003csup\u003e22\u003c/sup\u003e. CSF2 (GM-CSF) might promote arteriogenesis and neuroprotection after ischemic stroke \u003csup\u003e23\u003c/sup\u003e, however it also modulates macrophage and neutrophil activity and enhances pro-inflammatory cytokine release \u003csup\u003e24\u003c/sup\u003e. Both cytokines may thus contribute to immune dysregulation, exacerbated inflammation and neuronal damage in DCI.\u003c/p\u003e\n\u003cp\u003eThese results underscore a robust pro-inflammatory signature that emerges within the first 24 hours in patients developing DCI.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eNovel and underexplored markers:\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eOur study also identified less-characterized proteins that may represent novel contributors to DCI:\u003c/p\u003e\n\u003cp\u003eDOCK9, a member of the \u0026quot;Dedicator of Cytokinesis\u0026quot; family, is poorly characterized in CNS disease and neuroinflammation. While DOCK10 has been implicated in central nervous system immune signaling \u003csup\u003e25\u003c/sup\u003e, the significance of DOCK9 requires further investigation, and its expression may reflect broader dysregulation l or signaling changes in immune-active cells.\u003c/p\u003e\n\u003cp\u003eCLSTN3, also upregulated in DCI patients, has been recently associated with ferroptosis and iron metabolism, as part of the circAFF2\u0026ndash;CLSTN3\u0026ndash;miR-488 axis. It is implicated in neuronal death by downregulating miR-488, and it has been linked to ischemic stroke outcomes \u003csup\u003e26\u003c/sup\u003e. Its upregulation in DCI patients may reflect a susceptibility to iron-dependent cell death mechanisms triggered by hemoglobin breakdown and oxidative stress in the subarachnoid space and supporting a mechanistic link between hemorrhage burden and ischemic injury.\u003c/p\u003e\n\u003cp\u003eOther novel upregulated biomarker is XCL1, a chemokine ligand implicated in traumatic brain injury (TBI). In TBI models, XCL1 expression increases early peaking at 24 hours and contributing to secondary injury mechanisms \u003csup\u003e27\u003c/sup\u003e. Its elevation in DCI may reflect a similar neuroinflammatory damage following aSAH.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eFunctional Network Insights\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eSTRING-Cytoscape analysis revealed that several of the differentially expressed proteins, including MYL4, XCL1, CSF2, AHSP, and AMY2A/B function as central hub proteins with high interaction scores\u003cem\u003e.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThis supports the concept of coordinated dysregulation rather than isolated marker elevation, and suggests that systemic stress responses (e.g., hemoglobin metabolism, inflammation, immune cell activation) converge early in patients predisposed to DCI \u003csup\u003e28\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eLimitations and Future Directions\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eLimitations of this study include the small sample size without external validation, which restricts statistical power and generalizability. This analysis should be considered exploratory and hypothesis-generating. Moreover, we did not integrate cerebrospinal fluid (CSF) analyses, which could provide more localized inflammatory insights. Finally, longitudinal follow-up is needed to assess the predictive value of these proteins over time.\u003c/p\u003e\n\u003cp\u003eNonetheless, our findings provide a valuable foundation for future biomarker-driven studies. The observed dysregulation in both classical (e.g., CSF2, BGN, XCL1) and novel (e.g., CLSTN3, MYL4) proteins supports the hypothesis that DCI arises from a complex interplay between endothelial dysfunction, neuroinflammation, and metabolic failure.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eOur exploratory proteomic analysis identified a distinct set of differentially expressed proteins in aSAH patients who developed delayed cerebral ischemia (DCI) compared to those who did not. Among the identified biomarkers, BGN (a DAMP molecule linked to neuroinflammation), CSF2 (a key pro-inflammatory cytokine), and CLSTN3 (a novel protein potentially associated with ferroptosis and neuronal injury) emerged as the most promising candidates for further validation.\u003c/p\u003e\n\u003cp\u003eFuture studies in larger, multicenter cohorts are needed to validate their diagnostic and prognostic utility and to assess their potential for guiding early therapeutic interventions in patients at risk of DCI.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eCompliance with Journal Guidelines\u003c/em\u003e\u003c/strong\u003e\u003cem\u003e\u003cbr\u003e\u0026nbsp;We confirm that this manuscript complies with all instructions to authors as outlined by Neurocritical Care.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;Author Contributions\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cul type=\"disc\"\u003e\n \u003cli\u003e\u003cstrong\u003e\u003cem\u003eManel Santafé, MD:\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eStudy conception and design, drafting and writing of the manuscript, interpretation of results, discussion and conclusions.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003e\u003cem\u003eEstevo Santamarina, MD, PhD:\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eConceptualization, study supervision, writing of the manuscript, interpretation of results, discussion and conclusions\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003e\u003cem\u003eManuel Quintana, PhD:\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eStatistical analysis, methodological input, and study design discussions.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003e\u003cem\u003eAnna Penalba, PhD:\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eProteomic sample processing, biomarker analysis, manuscript revision.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003e\u003cem\u003eAnna Rosell, PhD\u003c/em\u003e\u003c/strong\u003e: Supervision of proteomic analysis, data interpretation, manuscript revision.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003e\u003cem\u003eLaura Abraira, MD, PhD:\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eManuscript review and editing.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003e\u003cem\u003eDaniel Campos-Fernandez, MD, PhD:\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eManuscript review and editing.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003e\u003cem\u003eAnna Sánchez, MD:\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eManuscript review and editing.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003e\u003cem\u003eRosa-Maria Gràcia, MD, PhD:\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eManuscript review and editing.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAuthorship Confirmation\u003c/em\u003e\u003c/strong\u003e\u003cem\u003e\u003cbr\u003e\u0026nbsp;We confirm that all authors meet the criteria for authorship in accordance with ICMJE recommendations, and all have approved the final version of the manuscript.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eOriginality Statement\u003c/em\u003e\u003c/strong\u003e\u003cem\u003e\u003cbr\u003e\u0026nbsp;We confirm that this manuscript has not been published elsewhere and is not currently under consideration by another journal.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eEthical Approval and Informed Consent\u003c/em\u003e\u003c/strong\u003e\u003cem\u003e\u003cbr\u003e\u0026nbsp;This study was approved by the Institutional Review Board (IRB) of Hospital Universitari Vall d’Hebron (IRB: PR(AG)212/2017). All procedures were conducted in accordance with ethical standards, and written informed consent was obtained from all participants or their legal surrogates. For this prospective study, IRB approval was obtained prior to sample and data analysis.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eConflict of Interest Disclosure\u003c/em\u003e\u003c/strong\u003e\u003cem\u003e\u003cbr\u003e\u0026nbsp;The authors declare no conflicts of interest relevant to this work.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eReporting Checklist\u003c/em\u003e\u003c/strong\u003e\u003cem\u003e\u003cbr\u003e\u0026nbsp;\u003cbr\u003e\u0026nbsp;This study follows the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) guidelines. All relevant items have been addressed in the manuscript.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eFunding\u003c/em\u003e\u003c/strong\u003e\u003cem\u003e\u003cbr\u003e\u0026nbsp;This study was supported by a research grant from the Fundación Eugenio Rodríguez Pascual (FERP-2022-1) and constitutes a project derived from that funded research. The grant specifically covered the costs related to the biomarker analysis\u003c/em\u003e\u003c/p\u003e"},{"header":" References","content":"\u003col\u003e\n \u003cli\u003eHoh BL, Ko NU, Amin-Hanjani S, et al. 2023 Guideline for the Management of Patients With Aneurysmal Subarachnoid Hemorrhage: A Guideline From the American Heart Association/American Stroke Association. Stroke 2023;54:e314-e70.\u003c/li\u003e\n \u003cli\u003eTreggiari MM, Rabinstein AA, Busl KM, et al. Guidelines for the Neurocritical Care Management of Aneurysmal Subarachnoid Hemorrhage. Neurocritical care 2023;39:1-28.\u003c/li\u003e\n \u003cli\u003eMayer SA, Kreiter KT, Copeland D, et al. Global and domain-specific cognitive impairment and outcome after subarachnoid hemorrhage. Neurology 2002;59:1750-8.\u003c/li\u003e\n \u003cli\u003eZaroff JG, Leong J, Kim H, et al. Cardiovascular predictors of long-term outcomes after non-traumatic subarachnoid hemorrhage. Neurocritical care 2012;17:374-81.\u003c/li\u003e\n \u003cli\u003evan der Bilt I, Hasan D, van den Brink R, et al. Cardiac dysfunction after aneurysmal subarachnoid hemorrhage: relationship with outcome. Neurology 2014;82:351-8.\u003c/li\u003e\n \u003cli\u003eRichard C. Stress-related cardiomyopathies. Ann Intensive Care 2011;1:39.\u003c/li\u003e\n \u003cli\u003eLee VH, Oh JK, Mulvagh SL, Wijdicks EF. Mechanisms in neurogenic stress cardiomyopathy after aneurysmal subarachnoid hemorrhage. Neurocritical care 2006;5:243-9.\u003c/li\u003e\n \u003cli\u003eFriedman JA, Pichelmann MA, Piepgras DG, et al. Pulmonary complications of aneurysmal subarachnoid hemorrhage. Neurosurgery 2003;52:1025-31; discussion 31-2.\u003c/li\u003e\n \u003cli\u003eHijdra A, Van Gijn J, Stefanko S, Van Dongen KJ, Vermeulen M, Van Crevel H. Delayed cerebral ischemia after aneurysmal subarachnoid hemorrhage: clinicoanatomic correlations. Neurology 1986;36:329-33.\u003c/li\u003e\n \u003cli\u003eHong CM, Tosun C, Kurland DB, Gerzanich V, Schreibman D, Simard JM. Biomarkers as outcome predictors in subarachnoid hemorrhage--a systematic review. Biomarkers 2014;19:95-108.\u003c/li\u003e\n \u003cli\u003ePrzybycien-Szymanska MM, Ashley WW, Jr. Biomarker Discovery in Cerebral Vasospasm after Aneurysmal Subarachnoid Hemorrhage. J Stroke Cerebrovasc Dis 2015;24:1453-64.\u003c/li\u003e\n \u003cli\u003eZhong FF, Wei B, Bao GX, et al. FABP3 Induces Mitochondrial Autophagy to Promote Neuronal Cell Apoptosis in Brain Ischemia-Reperfusion Injury. Neurotoxicity research 2024;42:35.\u003c/li\u003e\n \u003cli\u003eYing Z, Byun HR, Meng Q, et al. Biglycan gene connects metabolic dysfunction with brain disorder. Biochimica et biophysica acta Molecular basis of disease 2018;1864:3679-87.\u003c/li\u003e\n \u003cli\u003eWu Q, Wang XL, Yu Q, et al. Inflammasome Proteins in Cerebrospinal Fluid of Patients with Subarachnoid Hemorrhage are Biomarkers of Early Brain Injury and Functional Outcome. World Neurosurg 2016;94:472-9.\u003c/li\u003e\n \u003cli\u003eVergouwen MD, Vermeulen M, van Gijn J, et al. Definition of delayed cerebral ischemia after aneurysmal subarachnoid hemorrhage as an outcome event in clinical trials and observational studies: proposal of a multidisciplinary research group. Stroke 2010;41:2391-5.\u003c/li\u003e\n \u003cli\u003eRitchie ME, Phipson B, Wu D, et al. limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic acids research 2015;43:e47.\u003c/li\u003e\n \u003cli\u003eXu Z, Rui YN, Hagan JP, Kim DH. Intracranial Aneurysms: Pathology, Genetics, and Molecular Mechanisms. Neuromolecular medicine 2019;21:325-43.\u003c/li\u003e\n \u003cli\u003eSantiago-Sim T, Fang X, Hennessy ML, et al. THSD1 (Thrombospondin Type 1 Domain Containing Protein 1) Mutation in the Pathogenesis of Intracranial Aneurysm and Subarachnoid Hemorrhage. Stroke 2016;47:3005-13.\u003c/li\u003e\n \u003cli\u003eGarc\u0026iacute;a-Llorca A, Carta F, Supuran CT, Eysteinsson T. Carbonic anhydrase, its inhibitors and vascular function. Frontiers in molecular biosciences 2024;11:1338528.\u003c/li\u003e\n \u003cli\u003eYounes H, Kyritsi I, Mahrougui Z, Benharouga M, Alfaidy N, Marquette C. Effects of Prokineticins on Cerebral Cell Function and Blood-Brain Barrier Permeability. International journal of molecular sciences 2023;24.\u003c/li\u003e\n \u003cli\u003eBabelova A, Moreth K, Tsalastra-Greul W, et al. Biglycan, a danger signal that activates the NLRP3 inflammasome via toll-like and P2X receptors. The Journal of biological chemistry 2009;284:24035-48.\u003c/li\u003e\n \u003cli\u003eClark DN, Begg LR, Filiano AJ. Unique aspects of IFN-\u0026gamma;/STAT1 signaling in neurons. Immunological reviews 2022;311:187-204.\u003c/li\u003e\n \u003cli\u003eSugiyama Y, Yagita Y, Oyama N, et al. Granulocyte colony-stimulating factor enhances arteriogenesis and ameliorates cerebral damage in a mouse model of ischemic stroke. Stroke 2011;42:770-5.\u003c/li\u003e\n \u003cli\u003eSaita K, Moriuchi Y, Iwagawa T, et al. Roles of CSF2 as a modulator of inflammation during retinal degeneration. Cytokine 2022;158:155996.\u003c/li\u003e\n \u003cli\u003eNamekata K, Guo X, Kimura A, et al. Roles of the DOCK-D family proteins in a mouse model of neuroinflammation. The Journal of biological chemistry 2020;295:6710-20.\u003c/li\u003e\n \u003cli\u003eQi J, Meng C, Mo J, Shou T, Ding L, Zhi T. CircAFF2 Promotes Neuronal Cell Injury in Intracerebral Hemorrhage by Regulating the miR-488/CLSTN3 Axis. Neuroscience 2023;535:75-87.\u003c/li\u003e\n \u003cli\u003eCiechanowska A, Popiolek-Barczyk K, Ciapała K, et al. Traumatic brain injury in mice induces changes in the expression of the XCL1/XCR1 and XCL1/ITGA9 axes. Pharmacological reports : PR 2020;72:1579-92.\u003c/li\u003e\n \u003cli\u003eMollan TL, Yu X, Weiss MJ, Olson JS. The role of alpha-hemoglobin stabilizing protein in redox chemistry, denaturation, and hemoglobin assembly. Antioxidants \u0026amp; redox signaling 2010;12:219-31.\u003cem\u003e\u003c/em\u003e\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTables 1 to 2 are available in the Supplementary Files section\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"neurocritical-care","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"neca","sideBox":"Learn more about [Neurocritical Care](http://link.springer.com/journal/12028)","snPcode":"12028","submissionUrl":"https://www.editorialmanager.com/neca/default2.aspx","title":"Neurocritical Care","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-7203739/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7203739/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eBackground: \u003c/strong\u003e\u003c/em\u003e\u003cem\u003eDelayed cerebral ischemia (DCI) is a major cause of morbidity following aneurysmal subarachnoid hemorrhage (aSAH), yet early prediction remains challenging. This study aimed to identify blood-based protein biomarkers within 24 hours of ICU admission associated with DCI using high-throughput proteomics.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eMethods: \u003c/strong\u003e\u003c/em\u003e\u003cem\u003eWe conducted a prospective longitudinal study including 86 aSAH patients, of whom 28 developed DCI. For this exploratory analysis, we matched 8 patients who developed DCI with 8 controls without DCI based on age, sex, and severity scores. Plasma samples were analyzed using the Olink® Explore 3072 platform targeting 2,943 proteins. Differential expression analysis was performed using linear Bayesian models with FDR correction.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eResults: \u003c/strong\u003e\u003c/em\u003e\u003cem\u003eWe identified 15 significantly dysregulated proteins (p \u0026lt; 0.01) in DCI patients. Key downregulated proteins included THSD1, CA3, and PROK1—associated with vascular integrity and endothelial function. Upregulated proteins included BGN, IFNG, and CSF2—related to innate immunity and neuroinflammation. Novel candidates such as CLSTN3 and DOCK9 also showed altered expression. Protein-protein interaction and GO enrichment analyses revealed involvement in inflammatory, immune, and metabolic pathways.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eConclusions: \u003c/strong\u003e\u003c/em\u003e\u003cem\u003eOur findings suggest a distinct early molecular signature in aSAH patients who develop DCI, characterized by pro-inflammatory and neurovascular dysfunction markers. These candidate biomarkers warrant further validation in larger cohorts and may guide early risk stratification and therapeutic interventions.\u003c/em\u003e\u003c/p\u003e","manuscriptTitle":"Biomarker Differences in Aneurysmal Subarachnoid Hemorrhage: A Comparative Study of Patients With and Without Delayed Cerebral Ischemia","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-30 08:44:18","doi":"10.21203/rs.3.rs-7203739/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"","date":"2025-07-28T17:10:32+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-07-28T15:10:22+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"Neurocritical Care","date":"2025-07-28T13:56:05+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-07-25T13:09:43+00:00","index":"","fulltext":""},{"type":"submitted","content":"Neurocritical Care","date":"2025-07-24T11:30:08+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"neurocritical-care","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"neca","sideBox":"Learn more about [Neurocritical Care](http://link.springer.com/journal/12028)","snPcode":"12028","submissionUrl":"https://www.editorialmanager.com/neca/default2.aspx","title":"Neurocritical Care","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"a0ecc04a-112d-4e50-bf1a-6d731679cc57","owner":[],"postedDate":"July 30th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-11-24T16:03:36+00:00","versionOfRecord":{"articleIdentity":"rs-7203739","link":"https://doi.org/10.1007/s12028-025-02410-1","journal":{"identity":"neurocritical-care","isVorOnly":false,"title":"Neurocritical Care"},"publishedOn":"2025-11-21 15:58:37","publishedOnDateReadable":"November 21st, 2025"},"versionCreatedAt":"2025-07-30 08:44:18","video":"","vorDoi":"10.1007/s12028-025-02410-1","vorDoiUrl":"https://doi.org/10.1007/s12028-025-02410-1","workflowStages":[]},"version":"v1","identity":"rs-7203739","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7203739","identity":"rs-7203739","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}