# Acute ischemic stroke and reperfusion drive molecular immune-vascular activations detectable in peripheral blood

Francesca Rapido, Nicola Marchi, Julien Labreuche, Adrien ter Schiphorst, Marine Blaquière, Frédéric de Bock, Victoria Calcado, Julien Fendeleur, Philippe Marin, Pierre-François Perrigault, et al.

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## ► To cite this version:

Francesca Rapido, Nicola Marchi, Julien Labreuche, Adrien ter Schiphorst, Marine Blaquière, et al. Acute ischemic stroke and reperfusion drive molecular immune-vascular activations detectable in peripheral blood. Journal of Neurointerventional Surgery, 2025, pp.jnis-2025-023885. 10.1136/jnis-2025-023885. hal-05280563

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# Acute ischemic stroke and reperfusion drive molecular immune-vascular activations detectable in peripheral blood

Francesca Rapido ¹ ², Nicola Marchi ³, Julien Labreuche ⁴, Adrien Ter Schiphorst ⁵, Marine Blaquière ², Frédéric de Bock ², Victoria Calcado ⁶, Julien Fendeleur ⁶, Philippe Marin ², Pierre-François Perrigault ⁶, Marinette Moynier ⁷, Gerald Chanques ⁸ ⁹, Vincent Costalat ³ ⁷, Cyril Dargazanli ³ ⁷

¹ Department of Anesthesia and Critical Care Medicine, Gui de Chauliac University Hospital, Montpellier University Medical Center, Montpellier, France c-dargazanli@chu-montpellier.fr francesca.rapido@gmail.com Nicola.Marchi@igf.cnrs.fr v-costalat@chu-montpellier.fr.

² Institute of Functional Genomics (IGF), University of Montpellier, CNRS, INSERM, Montpellier, France.

³ Institute of Functional Genomics (IGF), University of Montpellier, CNRS, INSERM, Montpellier, France c-dargazanli@chu-montpellier.fr francesca.rapido@gmail.com Nicola.Marchi@igf.cnrs.fr v-costalat@chu-montpellier.fr.

⁴ Department of Biostatistics, CHU Lille, Lille, France.

⁵ Department of Neurology, Gui de Chauliac Hospital, Montpellier University Medical Center, Montpellier, France.

⁶ Department of Anesthesia and Critical Care Medicine, Gui de Chauliac University Hospital, Montpellier University Medical Center, Montpellier, France.

⁷ Department of Neuroradiology, Gui de Chauliac Hospital, Montpellier University Medical Center, Montpellier, France.

⁸ Department of Anesthesiology and Critical Care Medicine, Saint-Eloi Hospital, Montpellier University Medical Center, Montpellier, France.

⁹ PhyMedExp, INSERM, CNRS, University of Montpellier, Montpellier, France.

## Keywords:

Inflammation; Inflammatory Response; Thrombectomy.
# Abstract

**Background:**

Inflammation drives damage in acute ischemic stroke (AIS). Here, we map temporal and molecular mechanisms of immune-vascular response in patients with AIS treated with endovascular thrombectomy (EVT) for anterior circulation large-vessel occlusion.

**Methods:**

In this prospective cohort, 52 patients underwent serial peripheral blood sampling at groin puncture (Pre), catheter withdrawal (T0), and 6, 24, and 48 hours post-reperfusion. Thirteen immune and vascular players were quantified by mesoscale multiplex assays. Clinical outcomes were the modified Rankin Scale (mRS) score at 3 months and the National Institutes of Health Stroke Scale (NIHSS) at 24 hours.

**Results:**

Adjusted by age, baseline Alberta Stroke Program Early CT Score (ASPECTS) and NIHSS scores, higher pre-EVT peripheral blood levels of interleukin (IL)-1β, IL-4, IL-10, and IL-13 were associated with poorer 24-hours NIHSS. Post-EVT reperfusion, IL-6 and its downstream effectors vascular cell adhesion molecule- (VCAM-1) and intercellular adhesion molecule-1 (ICAM-1) levels rose in peripheral blood over time, suggesting cerebrovascular inflammation, accompanied by the increased levels of acute-phase reactants C-reactive protein (CRP) and serum amyloid A (SAA), indicative of a systemic inflammatory engagement. In the same timeframe, interferon-gamma (IFN-γ) blood levels decreased. Adjusted by age, baseline ASPECT and NIHSS scores, and pre-thrombectomy biomarker levels, higher post-EVT levels of IL-6, VCAM-1, ICAM-1, and SAA were associated with poorer 24-hours NIHSS and unfavorable mRS 3 month outcomes, supporting an evolving immune dysregulation following AIS.

**Conclusion:**

This exploratory study points to immune and vascular activation mechanisms from pre- to post-EVT, representing possible disease indicators and targets.
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Introduction

Acute ischemic stroke (AIS) is a leading cause of mortality and disability worldwide. 1 Endovascular thrombectomy (EVT) has advanced the management of large-vessel occlusion (LVO) strokes, improving reperfusion rates and clinical outcomes. Recent research leveraged EVT to obtain biological samples and identify molecular and cellular consequences of LVO. 2–6 Accumulating evidence suggests that LVO elicits a local brain acute inflammatory response, playing a role in ischemic injury, reperfusion-associated damage, and possibly modifying neurological recovery. 2 This response is multifactorial, involving the participation of glial cells and blood-brain barrier (BBB) dysfunction, as well as the local activation of leukocytes. 4,7 The acute phase of AIS is associated with an intracranial blood inflammatory response, concerted by soluble factors and leukocytes, 3 5 6 8 possibly linked to infarct progression and outcomes. 9 10

Despite these associations the temporal dynamics of immune and vascular molecular changes, from before to after reperfusion, remain insufficiently characterized. 11 Emerging studies have attempted to outline this inflammatory response; however, limitations persist, such as the use of a single time point or restricted analytical capacity, which reduces the ability to capture complex molecular dynamics. Importantly, pre-reperfusion measurements of inflammatory
status are necessary to distinguish between stroke induced and reperfusion-driven immune responses. 2 12 13 These knowledge gaps limit the identification of disease biomarkers and the development of therapeutic interventions that could complement mechanical thrombectomy.

In this exploratory study, we tracked the temporal evolution of immunological and vascular
molecular players captured in the peripheral blood from immediately before to post-
intervention, up to 48 hours, in a monocentric cohort of AIS patients with anterior LVO. We
outline potential mechanistic links and the association between the trajectories of biomarkers
and longterm disability, as defined by the modified Rankin Scale (mRS) score at 3 months,
and early neurological improvement, assessed by the National Institutes of Health Stroke
Scale (NIHSS) at 24 hours. We report the temporal coordination of immune mediators, along
with molecular biomarkers of vascular activation, thereby outlining disease players and their
associations with patient outcomes.

**Materials and methods**

Study design and population

This study is a prospective ancillary investigation associated with the Multimodal Analysis of
the Origin of Intracranial Thrombi (MISO) project (NCT04421326, RECHMPL1880236, ID-
RCB 2018-A02651-54). It was conducted as a single-center, longitudinal study with ethical
approval obtained from the institutional review board (CPP# 2019.10.04_19.07.30.36737).
Patients were eligible if they were 18 years or older, had an AIS due to LVO of the anterior
circulation, and underwent EVT. Intravenous thrombolysis was permitted according to current
guidelines. Patients were excluded if they were referred from another center due to potential
heterogeneity in clinical management and reduced feasibility of collecting longitudinal blood
samples beyond the acute phase. Other exclusion criteria included hemoglobin level <7.0
g/dL (or <9.0 g/dL with cardiorespiratory comorbidities), active infections, malignancies,
chronic antiinflammatory treatment, pre-stroke mRS >3, or legal protection status.

**Patient management**

All patients underwent EVT in a dedicated neuroangiography suite with an anesthesia team available throughout the procedure, regardless of the anesthesia modality. The choice between general anesthesia (GA) and local anesthesia (LA) was based on the patient's clinical evaluation. EVT was performed using stent retrievers and aspiration techniques according to standard neurointerventional protocols, as previously described.⁴ In cases of tandem occlusions, a retrograde approach was generally preferred, prioritizing intracranial reperfusion before addressing the cervical carotid lesion. Reperfusion success was assessed using the modified Thrombolysis in Cerebral Infarction (mTICI) score, with successful reperfusion defined as mTICI ≥2b.
## Outcome assessment and definition

Functional outcomes were assessed using the mRS at 90 days (±15 days) post-stroke and the NIHSS at 24 hours (secondary outcome), as reported by neurologists or neuroradiologists during face-to-face interviews or telephone conversations with patients, relatives, or general practitioners. A favorable outcome was defined as mRS 0 to 2. For exploratory data visualization, we further stratified patients into three pre-specified mRS categories (0–2, 3–4, 5–6) to display biomarker distributions across increasing disability levels.

## Blood sampling and processing

Peripheral blood samples were collected at five time points: before EVT during femoral artery puncture (Pre), at the time of catheter withdrawal after recanalization (T0), and at 6, 24, and 48 hours post-reperfusion (T6, T24, T48) (online supplemental figure 1). Pre- and T0 samples were obtained from arterial blood, while later time points used venous blood. Blood samples were collected in 5 mL ethylene diamine tetra acetic acid (EDTA) coated tubes, gently inverted to ensure uniform anticoagulation, and stored at 4°C until processing. Plasma was separated via centrifugation at 2,000×g for 10 minutes at 4°C, aliquoted, and stored at -80°C for cytokine analysis. Cytokine and vascular injury markers were quantified using Meso Scale Discovery (MSD) MULTI-ARRAY V-PLEX electrochemiluminescence-based assays (Meso Scale Diagnostics, LLC., Rockville, MD, USA). Pro- and anti-inflammatory markers (IL-1β, IL-2, IL-6, IL-8, TNF-α, IFN-γ, CRP, SAA, IL-4, IL-10, IL-13) and vascular injury markers (VCAM-1, ICAM-1) were assessed following the manufacturer's protocol. The IL-6/IL-10 ratio, an indicator of immune dysregulation, was calculated for each patient.

## Statistical analysis

Data are presented as the median (interquartile range (IQR)) for quantitative variables and numbers (percentage) for categorical variables. The evolution of each biomarker over time was assessed using a linear mixed model, including time points as a 5-level categorical variable (using the pre-thrombectomy measures as baseline reference values) with an unstructured covariance pattern to account for the intra-subject correlation.

Except for ICAM-1, a log transformation was applied to reduce the skewness of distributions and satisfy the normality of model residuals. Standardized effect sizes (ES) of post-thrombectomy changes from baseline were calculated from regression coefficients of linear mixed models by their standard errors to allow comparisons of the different biomarkers. Partial Spearman's rank correlation coefficients (r) were used to explore associations between 90-day mRS and pre-EVT biomarker levels, after prespecified adjustment for age, baseline Alberta Stroke Program Early CT Score (ASPECTS) and NIHSS scores. For biomarkers with significant post-EVT changes, partial Spearman correlations were calculated between 90-day mRS and peak post-EVT variations, by adjusting for pre-specified confounders and preEVT biomarker levels. We performed the same analyses using NIHSS at 24 hours as a secondary outcome. Absolute r values <0.3 were interpreted as small correlations and 95% confidence intervals (CIs) of r were estimated using the Fisher Z transformation. Statistical testing was conducted at the two-tailed α-level of 0.05. No correction for multiple testing was applied due to the explorative nature of the study. Analyses were performed using SAS version 9.4 (SAS Institute, Cary, NC, USA).
<table><caption>**Table 1** Main baseline characteristics and outcomes</caption><thead><tr><th>Baseline characteristics</th><th>Values</th></tr></thead><tbody><tr><td>Age, years</td><td>78 (67–85)</td></tr><tr><td>Men</td><td>34 (65.4)</td></tr><tr><td>BMI, kg/m², mean (SD)</td><td>26 (4)</td></tr><tr><td>Medical history</td><td></td></tr><tr><td>Hypertension</td><td>28 (53.8)</td></tr><tr><td>Active smoking</td><td>12 (23.1)</td></tr><tr><td>Dyslipidemia</td><td>11 (21.2)</td></tr><tr><td>Atrial fibrillation</td><td>10 (19.2)</td></tr><tr><td>Myocardial infarction</td><td>6 (11.5)</td></tr><tr><td>Alcohol addiction</td><td>5 (9.6)</td></tr><tr><td>Heart failure</td><td>6 (11.5)</td></tr><tr><td>Coronary stent</td><td>5 (9.6)</td></tr><tr><td>Diabetes</td><td>4 (7.7)</td></tr><tr><td>Prior stroke</td><td>5 (9.6)</td></tr><tr><td>Examination findings at admission</td><td></td></tr><tr><td>Pre-stroke mRS score</td><td></td></tr><tr><td>0</td><td>40 (76.9)</td></tr><tr><td>1</td><td>8 (15.4)</td></tr><tr><td>&gt;1</td><td>4 (7.7)</td></tr><tr><td>NIHSS score</td><td>17 (10–22)</td></tr><tr><td>ASPECTS*</td><td>8 (7–10)</td></tr><tr><td>Baseline infarct volume, ml<sup>†</sup></td><td>113 (55–139)</td></tr><tr><td>Baseline infarct volume, ml<sup>†</sup></td><td>113 (55–139)</td></tr><tr><td>Systolic blood pressure, mmHg, mean (SD)</td><td>150 (138–163)</td></tr><tr><td>Leukocyte count, G/L<sup>‡</sup></td><td>8.17 (6.2–10.6)</td></tr><tr><td>Platelet count, G/L<sup>‡</sup></td><td>217 (170–256)</td></tr><tr><td>Hemoglobin, g/dL<sup>d</sup></td><td>13.6 (12.6–14.8)</td></tr><tr><td>Etiology*</td><td></td></tr><tr><td>Embolic</td><td>34 (65.4)</td></tr><tr><td>Atheromatous</td><td>11 (21.2)</td></tr><tr><td>Mixed (embolic and atheromatous)</td><td>4 (7.7)</td></tr><tr><td>Undetermined</td><td>2 (3.8)</td></tr><tr><td>Laterality right</td><td>24 (46.1)</td></tr><tr><td>Occlusion site</td><td></td></tr><tr><td>M1</td><td>22 (42.3)</td></tr><tr><td>M2</td><td>8 (15.4)</td></tr><tr><td>M1-M2</td><td>4 (7.7)</td></tr><tr><td>Tandem</td><td>18 (34.6)</td></tr><tr><td>General anesthesia</td><td>18 (34.6)</td></tr><tr><td>Symptom onset to groin puncture, min*</td><td>190 (135–329)</td></tr><tr><td>Intravenous rtPA thrombolysis</td><td>20 (38.5)</td></tr></tbody></table>

Continued
<table><caption>Table 1 Continued</caption><thead><tr><th>Baseline characteristics</th><th>Values</th></tr></thead><tbody><tr><td>Outcomes</td><td></td></tr><tr><td>mTICI ≥2b</td><td>52 (100)</td></tr><tr><td>Symptom onset to successful reperfusion time, min*</td><td>222 (165-360)</td></tr><tr><td>mRS score at 90 days*</td><td>2 (1 to 4)</td></tr><tr><td>Favorable outcome (mRS 0-2)</td><td>30 (58.8)</td></tr><tr><td>NIHSS at 24 hours</td><td>6(2-16)</td></tr><tr><td>Any ICH</td><td>22 (42.3)</td></tr><tr><td>Symptomatic ICH</td><td>2 (3.8)</td></tr><tr><td colspan="2">Values are number (%) or median (IQR).</td></tr><tr><td colspan="2">*1 missing value.</td></tr><tr><td colspan="2">†4 missing values.</td></tr><tr><td colspan="2">‡2 missing values.</td></tr><tr><td colspan="2">ASPECTS, Alberta Stroke Program Early CT Score; BMI, body mass index; ICH, Intracerebral hemorrhage; min, minute; mRS, modified Rankin Scale; mTICI, modified thrombolysis in cerebral infarction; NIHSS, National Institutes of Health Stroke Scale; rtPA, recombinant tissue plasminogen activator; SD, standard deviation.</td></tr></tbody></table>

# Results

## Baseline characteristics and stroke severity

We included 52 patients with anterior circulation LVO stroke treated by EVT in our tertiary stroke center between June 2021 and March 2024 (a detailed flow chart is provided in online supplemental figure 2). Baseline characteristics and outcomes are summarized in table 1. The median age was 78 (IQR, 67-85), and 65.4% of patients were male. Median NIHSS and ASPECT scores at admission were 17 (IQR, 10-22) and 8 (IQR, 7-10), respectively. Moreover, 46.1% of strokes were right-sided, and 42.3% involved the M1 segment of the middle cerebral artery. Tandem occlusions were observed in 34.6% of patients. Successful reperfusion (mTICI ≥2b) was achieved for all patients. At 24 hours, median NIHSS was 6 (IQR, 2-16). At 90 days, 30 of 51 evaluable patients (58.8%) had a favorable outcome, defined as an mRS score 0-2.

## Temporal trajectories of immune-vascular players in AIS detected in peripheral blood

The concentrations of immunological and vascular players measured in peripheral blood before intervention and at four consecutive time points following EVT are reported in table 2 (and graphically represented in online supplemental figure 3A-C). The forest plot (figure 1) illustrates the temporal evolution of each biomarker, expressed as standardized effect size (ES) to facilitate comparison. The pro-inflammatory cytokine IL-6 increased after reperfusion, as tracked up to 48 hours (ES+5.48, 95% CI: 3.52 to 7.44, P<0.0001). This was
accompanied by rising blood levels of the vascular adhesion molecules. In particular, VCAM-1 showed a progressive increase from T0 to T48 (ES+4.67, 95% CI: 2.71 to 6.63, P=0.007), hinting at concerted vascular-immune activation. In line with inflammatory cascades and propagations,14 the blood levels of hepatic-borne acute-phase factors serum amyloid A (SAA) and C-reactive protein (CRP) significantly increased over time, as measured up to T48 (SAA: ES+7.39, 95% CI: 5.43 to 9.35; CRP: ES+5.67, 95% CI: 3.71 to 7.63; both P<0.0001). The level of the anti-inflammatory cytokine IL-10 remained unchanged. We also observed a transient increase in IL-13 at T0 (ES+2.73, 95% CI: 0.77 to 4.69, P=0.019). We report a decrease in IFN-γ blood levels (ES -4.41, 95% CI: -6.37 to -2.45, P<0.0001), along with previous findings.15 The temporal dynamics of multiple mediators reflect immune-vascular activations in AIS, with a possible brain-peripheral interplay that is detectable through longitudinal peripheral blood sampling.

<table><caption>**Table 2** Median (25th to 75th percentiles) concentrations of peripheral blood biomarkers across different time points following endovascular treatment</caption><thead><tr><th rowspan="2">Biomarkers</th><th colspan="5">Time points from thrombectomy</th></tr><tr><th>PRE (n=51)</th><th>T0 (end of EVT)(n=52)</th><th>T6 (n=51)</th><th>T24 (n=52)</th><th>T48 (n=46)</th></tr></thead><tbody><tr><td colspan="6"><strong>Pro-inflammatory cytokines</strong></td></tr><tr><td>IL-1β, pg/ml</td><td>0.11<br>(0.00;0.21)</td><td>0.098 (0.03; 0.16)</td><td>0.095 (0.03;0.16)</td><td>0.117 (0.02;0.23)</td><td>0.148 (0.03;0.33)</td></tr><tr><td>IL-2, pg/ml</td><td>0.235<br>(0.04;0.48)</td><td>0.256 (0.04;0.58)</td><td>0.28 (0.00;0.65)</td><td>0.414 (0.05;0.75)</td><td>0.374 (0.08;0.67)</td></tr><tr><td>IL-6, pg/ml</td><td>3.58<br>(2.11;6.85)</td><td>4.16<br>(1.84;7.18)</td><td>5.51<br>(3.50;8.74)</td><td>7.43<br>(4.00;13.30)</td><td>9.35 (4.71;14.6)</td></tr><tr><td>IL-8, pg/ml</td><td>7.23<br>(5.16;10.40)</td><td>10 (6.89;16.10)</td><td>8.91<br>(5.72;12.70)</td><td>7.79<br>(4.86;11.10)</td><td>7.85 (5.34;12.80)</td></tr><tr><td>TNF-α, pg/ml</td><td>2.16<br>(1.46;3.24)</td><td>2.48<br>(1.52;3.68)</td><td>2.28<br>(1.49;3.72)</td><td>2.42<br>(1.38;3.44)</td><td>2.28 (1.37;3.54)</td></tr><tr><td>IFN-γ, pg/ml</td><td>5.47 (2.60;10.30)</td><td>2.26 (0.02;7.18)</td><td>1.80 (0.02;5.52)</td><td>2.07 (0.01;7.25)</td><td>3.14 (0.01;7.12)</td></tr><tr><td>CRP, ng/ml</td><td>3159 (2109;13128)</td><td>3721 (2064;12042)</td><td>4019 (2473;14557)</td><td>5853 (3133;21977)</td><td>18 253 (2991;47468)</td></tr><tr><td>SAA, ng/ml</td><td>6666 (2672;18412)</td><td>4957 (2046;32060)</td><td>7328 (3619;47866)</td><td>17 231 (8439;61849)</td><td>42 116 (19024;130596)</td></tr><tr><td colspan="6"><strong>Anti-inflammatory or immunoregulatory cytokines</strong></td></tr><tr><td>IL-4, pg/ml</td><td>0.02 (0.01;0.06)</td><td>0.03 (0.01;0.06)</td><td>0.02 (0.01;0.04)</td><td>0.03 (0.01;0.05)</td><td>0.03 (0.01;0.05)</td></tr><tr><td>IL-10, pg/ml</td><td>0.6 (0.38;1.84)</td><td>1.07<br>(0.44;2.13)</td><td>0.51<br>(0.33;1.15)</td><td>0.51<br>(0.37;0.90)</td><td>0.56 (0.36;1.00)</td></tr><tr><td>IL-13, pg/ml</td><td>0.77 (0.00;1.92)</td><td>1.25<br>(0.00;2.02)</td><td>0.81 (0.00;1.66)</td><td>0.86 (0.00;1.53)</td><td>0.96 (0.17;1.59)</td></tr><tr><td colspan="6"><strong>Endothelial activation and immune cells recruitment</strong></td></tr><tr><td>ICAM-1, ng/ml</td><td>572 (426;709)</td><td>577 (408;846)</td><td>600 (462;790)</td><td>595 (444;822)</td><td>633 (444;804)</td></tr><tr><td>VCAM-1, ng/ml</td><td>646 (477;962)</td><td>678 (466;943)</td><td>704<br>(541;1355)</td><td>867<br>(578;3332)</td><td>842 (550;5242)</td></tr></tbody><tfoot><tr><td colspan="6">CRP, C-reactive protein; ICAM-1, intercellular adhesion molecule-1; IFN-γ, Interferon-gamma; IL-2, Interleukin-2; IL-4, Interleukin-4; IL-6, Interleukin-6; IL-8, Interleukin-8; IL-10, Interleukin-10; IL-13, Interleukin-13; IL-1β, Interleukin-1 beta; SAA, Serum amyloid A; TNF-α, Tumor necrosis factor-alpha; VCAM-1, Vascular cell adhesion molecule-1.</td></tr></tfoot></table>

## Correlations between pre- and post-AIS biomarker blood levels and clinical outcomes

We investigated the association between pre-thrombectomy baseline biomarker concentrations and clinical outcomes (figure 2A,B). Adjusted by age, baseline ASPECT and NIHSS scores, significant associations were observed between higher pre-thrombectomy levels of IL-1β (r=0.38, 95% CI: 0.10 to 0.60, P=0.008), IL-4 (r=0.36, 95% CI: 0.07 to 0.59, P=0.013), IL-10 (r=0.39, 95% CI: 0.10 to 0.61, P=0.007), and IL-13 (r=0.32, 95% CI: 0.03 to 0.56, P=0.027) with NIHSS at 24 hours (figure 2B). Next, we correlated the post-EVT biomarker peak levels in peripheral blood (see table 2 and figure 1) with functional outcomes (figure 2C,D). Adjusted by age, baseline ASPECT and NIHSS scores, and pre-EVT biomarker levels, we report that post-EVT higher concentrations of IL-6, SAA, ICAM-1, and VCAM-1 were significantly associated with mRS 90 (figure 2C) and NIHSS (figure 2D).
Specifically, for correlations with mRS 3 months: IL-6 (r=0.35, 95% CI: 0.02 to 0.60, P=0.031), SAA (r=0.30, 95% CI: -0.02 to 0.57, P=0.061), ICAM-1 (r=0.33, 95% CI: 0.008 to 0.60, P=0.042), VCAM-1 (r=0.38, 95% CI: 0.06 to 0.62, P=0.017). Correlations with NIHSS 24-hours: IL-6 (r=0.35, 95% CI: 0.03 to 0.60, P=0.027), SAA (r=0.41, 95% CI: 0.10 to 0.64, P=0.008), ICAM-1 (r=0.33, 95% CI: 0.01 to 0.59, P=0.036), VCAM-1 (r=0.36, 95% CI: 0.05 to 0.61, P=0.02). In summary, depending on their preto post-EVT profiling, the blood levels of specific immune-vascular mediators correlate with the selected outcome measures (figure 3).

<figure><img src="image_4.png" /><figcaption>**Figure 1** Temporal changes in immune and vascular factors from pre- to 48 hours post-thrombectomy in peripheral blood. A forest plot illustrates the change in inflammation biomarkers from pre-thrombectomy levels to four post-thrombectomy time points (T0, T6, T24, T48) expressed as standardized effect sizes. Except for ICAM-1, a log transformation was applied to the biomarkers to normalize the residuals. P-values for comparisons between the time points are provided for each biomarker.</figcaption></figure>
<figure><img src="image_5.png" /></figure>

<figure><img src="image_6.png" /></figure>

<figure><img src="image_7.png" /></figure>

<figure><img src="image_8.png" /></figure>

**Figure 2** Correlation between immune and vascular activations and functional outcomes. A-B. Partial Spearman's rank correlation (95% CI) adjusted for age, baseline Alberta Stroke Program Early CT (ASPECT) and National Institutes of Health Stroke Scale (NIHSS) scores. A. Pre-thrombectomy biomarker levels and correlations to 3 month modified Rankin Scale (mRS); B. Pre-thrombectomy biomarker levels and correlations to NIHSS score at 24 hours. C-D. Partial Spearman's rank correlation (95% CI) adjusted for age, baseline ASPECT score, baseline NIHSS score, and pre-biomarker thrombectomy level. C. Peak post-thrombectomy biomarker variations and correlations to 3 month mRS. The peak variation was observed at T48 for all biomarkers, except for IFN-γ (T6), IL-10 (T24), and IL-13 (T0). D. Peak post-thrombectomy biomarker variations and correlations to NIHSS at 24 hours. The same peak time points were used as in (C).

<figure><img src="image_9.png" /></figure>

**Figure 3** Schematic representation of immune-vascular activation occurring in acute ischemic stroke (AIS) and reperfusion over time, detectable in peripheral blood. Graphical summary of peripheral immune-vascular dynamics in patients with large-vessel occlusion (LVO) undergoing endovascular thrombectomy (EVT). The figure illustrates the temporal evolution of selected blood biomarkers from pre-EVT to 48 hours post-reperfusion. Pre-EVT levels of IL-1β, IL-4, IL-10, and IL-13 correlate with early neurological status (National Institutes of Health Stroke Scale (NIHSS) at 24 hours), while post-EVT elevations in IL-6, SAA, ICAM-1, and VCAM-1 correlate with both early (NIHSS at 24 hours) and long-term (modified Rankin Scale (mRS) score at 90 days) outcomes. The rise in vascular (VCAM-1, ICAM-1) and inflammatory markers (CRP, SAA), alongside decreased IFNγ, reflects a dynamic and potentially maladaptive immune response detectable over time. These associations do not imply causality, and they may reflect the extent of ischemic injury. Created with BioRender.com
Interestingly, SAA was experimentally shown to reduce IFN-γ production.<sup>23 24</sup> Furthermore, experimental data indicate that AIS induces apoptosis of IFN-γ-producing T-cells in lymphoid tissues, contributing to stroke-associated immunosuppression.<sup>25-28</sup> The concerted and temporal action of these multiple players is graphically illustrated in figure 3.

We recognized that, while our results show significant associations between vascular-inflammatory markers and clinical outcomes, causality cannot be inferred. Biomarker elevations may in part reflect the severity of the ischemic injury, acting as correlates rather than causal mediators. Notably, in our analyses, associations with 24-hour NIHSS were adjusted for baseline stroke severity (figure 2B and D), supporting a potential relevance for biomarkers beyond initial infarct burden. Even as reactive markers, they remain relevant for biological interpretation and potentially for clinical stratification. Nonetheless, larger cohorts and mediation analyses are required to clarify the mechanistic role of these immune responses in stroke pathophysiology.

## Immune imbalances in AIS and potential pathophysiological role

Our results suggest that endogenous and homeostatic antiinflammatory mechanisms (eg, IL10) are not activated early after reperfusion, a period marked by a pro-inflammatory surge, particularly in IL-6, SAA, VCAM-1, and ICAM-1.<sup>26</sup> In a previous cohort of stroke patients treated, IL-10 levels rose gradually, reaching a peak on day 7 after medical intervention.<sup>27</sup> In our settings, a delayed IL-10 surge should, therefore, be explored.<sup>27</sup> Here we discussed that, in the timeframe we examined, the IL-6/ IL-10 ratio increased, with higher values observed in patients with severe outcomes (mRS 5-6). Although these comparisons (see online supplemental figures 4-6) lack statistical power due to the low number of patients in this subgroup, the trend supports the hypothesis that an early pro- and anti-inflammatory IL-6/ IL-10 imbalance may indicate immune dysregulation leading to severe impairments. A focused study is needed to elucidate these exact trajectories from early to long-term post-AIS.

We also report that, pre-EVT, higher levels of IL-4 and IL-13 were associated with poor early outcomes. These immune-regulatory cytokines could reflect an endogenous attempt to modify a pro-inflammatory cascade driven by IL-1β, specifically pre-EVT. Furthermore, circulating IL-4 has been shown to increase progressively over the first days after stroke onset,<sup>28</sup> suggesting that the re-exposure of the hypoperfused penumbral tissue following EVT may offset this anti-inflammatory signal. Experimental work supports a reparative and neuroprotective role for both IL-4 and IL-13.<sup>28-30</sup> The possibility of an immune imbalance supports studying peri-procedural immunomodulation, for example, to amplify endogenous anti-inflammatory pathways and control vascular activations, thereby re establishing a timely counter-regulatory response.

## Study limitations

Our study had some limitations. First, no formal sample size calculation was done, and we caution that the sample size remains limited. Cytokine measurements were focused on the first 48 hours post-reperfusion, preventing the assessment of the longer-term mechanisms. We did not cross-compare with intracranial blood samples, and more comprehensive molecular
panels could be employed. Additionally, all patients achieved successful reperfusion, meaning our findings may not apply to patients with incomplete or failed reperfusion. Finally, this was a single-center study, and not all eligible patients were included due to logistical constraints, which could introduce selection bias. Future research should corroborate these findings in a larger population, with both intracranial and peripheral sampling, with extended follow-up and complementary imaging to better link these biomarkers with clinical outcomes.

## Conclusion

Our study links a number of immune-vascular players in AIS, from pre- to post-EVT. Notably, the IL-6, VCAM-1, and ICAM-1 patterns support an involvement of endothelial activation, a clue for possible loss of BBB stability. Our results support the framework of an inflammatory response involving the periphery, characterized by increased SAA and CRP blood levels, at least in the early post-EVT timeframe we examined. Together, these findings advance our understanding of immune-vascular changes in AIS and support future work to evaluate disease indicators and potential immunomodulatory strategies to improve recovery.

## Acknowledgements

The authors thank the patients and clinical staff who contributed to this study.

## Contributors

FR conceived and designed the study, coordinated clinical implementation and regulatory approvals, managed data processing and visualization, and led the drafting and critical revision of the manuscript. NM contributed to the study design, supervised biomarker analyses, and participated in biological data interpretation and manuscript drafting. JL performed the statistical analyses, contributed to data interpretation, and revised the manuscript. FR, ATS, and CD managed patient inclusion and coordinated blood sample collection during the acute phase. ATS, MB, FDB, VC, JF, and PM contributed to data acquisition, clinical coordination, regulatory aspects, and laboratory procedures. PFP provided institutional oversight and contributed to study coordination during its early phase. MM provided implementation of protocol approval and patient inclusion. VC, CD, and GC supervised the study, contributed to its design and implementation, and critically revised the manuscript. FR is the guarantor.

## Funding

This study was funded in part by Stryker Neurovascular and Fondation pour la Recherche AVC (FRM AVC202408019937).

## Competing interests

None declared.
**Patient consent for publication**

Not applicable.

**Ethics approval**

This study involves human participants and was approved by the institutional review board (CPP# 2019.10.04_19.07.30.36737) as part of the Multimodal Analysis of the Origin of Intracranial Thrombi (MISO) project (NCT04421326, RECHMPL1880236, ID-RCB 2018-A02651-54). It was conducted as a single-center, longitudinal study, and all participants provided written informed consent before inclusion.

**Provenance and peer review**

Not commissioned; externally peer reviewed.

**Data availability statement**

Data are available upon reasonable request.

**References**

1 Feigin VL, et al. Global, regional, and national burden of stroke and its risk factors, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019. Lancet Neurol 2021;20:795.

2 Couch C, Mallah K, Borucki DM, et al. State of the science in inflammation and stroke recovery: A systematic review. *Ann Phys Rehabil Med* 2022;65:101546.

3 Shaw BC, Maglinger GB, Ujas T, et al. Isolation and identification of leukocyte populations in intracranial blood collected during mechanical thrombectomy. *J Cereb Blood Flow Metab* 2022;42:280–91.

4 Dargazanli C, Blaquière M, Moynier M, et al. Inflammation biomarkers in the intracranial blood are associated with outcome in patients with ischemic stroke. *J NeuroIntervent Surg* 2025;17:159–66.

5 Martha SR, Cheng Q, Fraser JF, et al. Expression of Cytokines and Chemokines as Predictors of Stroke Outcomes in Acute Ischemic Stroke. *Front Neurol* 2019;10:1391.

6 Maglinger B, Sands M, Frank JA, et al. Intracranial VCAM1 at time of mechanical thrombectomy predicts ischemic stroke severity. *J Neuroinflammation* 2021;18:109.
7 Giannoni P, Badaut J, Dargazanli C, et al. The pericyte–glia interface at the blood–brain barrier. *Clin Sci* 2018;132:361–74.

8 Mengel A, Ulm L, Hotter B, et al. Biomarkers of immune capacity, infection and inflammation are associated with poor outcome and mortality after stroke – the PREDICT study. *BMC Neurol* 2019;19:148.

9 Montellano FA, Ungethüm K, Ramiro L, et al. Role of Blood-Based Biomarkers in Ischemic Stroke Prognosis: A Systematic Review. *Stroke* 2021;52:543–51.

10 Schweizer J, Bustamante A, Lapierre-Fétaud V, et al. SAA (Serum Amyloid A): A Novel Predictor of Stroke-Associated Infections. *Stroke* 2020;51:3523–30.

11 Soldozy S, Yağmurlu K, Norat P, et al. Biomarkers Predictive of Long-Term Outcome After Ischemic Stroke: A Meta-Analysis. *World Neurosurg* 2022;163:e1–42.

12 Du M, Xu L, Zhang X, et al. Association Between Inflammatory Burden Index and Unfavorable Prognosis After Endovascular Thrombectomy in Acute Ischemic Stroke. *J Inflamm Res* 2023;16:3009–17.

13 Wang H, Tian X, Liao Z, et al. Inflammatory biomarkers may be associated with poor outcomes after mechanical thrombectomy. *Thromb J* 2024;22:58.

14 Hagihara K, Nishikawa T, Isobe T, et al. IL-6 plays a critical role in the synergistic induction of human serum amyloid A (SAA) gene when stimulated with proinflammatory cytokines as analyzed with an SAA isoform real-time quantitative RT-PCR assay system. *Biochem Biophys Res Commun* 2004;314:363–9.

15 Jagdmann S, Berchtold D, Gutbier B, et al. Efficacy and safety of intratracheal IFN-γ treatment to reverse stroke-induced susceptibility to pulmonary bacterial infections. *J Neuroimmunol* 2021;355:577568.

16 Maglinger B, Harp JP, Frank JA, et al. Inflammatory-associated proteomic predictors of cognitive outcome in subjects with ELVO treated by mechanical thrombectomy. *BMC Neurol* 2023;23:214.

17 Bustamante A, Sobrino T, Giralt D, et al. Prognostic value of blood interleukin-6 in the prediction of functional outcome after stroke: a systematic review and meta-analysis. *J Neuroimmunol* 2014;274:215–24.

18 Deng Q-W, Huang S, Li S, et al. Inflammatory Factors as Potential Markers of Early Neurological Deterioration in Acute Ischemic Stroke Patients Receiving Endovascular Therapy - The AISRNA Study. *J Inflamm Res* 2021;14:4399–407.

19 Mechtouff L, Bochaton T, Paccalet A, et al. Association of Interleukin-6 Levels and Futile Reperfusion After Mechanical Thrombectomy. *Neurology (ECronicon)* 2021;96:e752–7.

20 McCabe JJ, Walsh C, Gorey S, et al. Interleukin-6, C-Reactive Protein, and Recurrence After Stroke: A Time-Course Analysis of Individual-Participant Data. *Stroke* 2024;55:2825–34.
21 Nian K, Harding IC, Herman IM, et al. Blood-Brain Barrier Damage in Ischemic Stroke and Its Regulation by Endothelial Mechanotransduction. *Front Physiol* 2020;11:605398.

22 Faura J, Bustamante A, Miró-Mur F, et al. Stroke-induced immunosuppression: implications for the prevention and prediction of post-stroke infections. *J Neuroinflammation* 2021;18:127.

23 He M, Liu Y, Chen S, et al. Serum amyloid A promotes glycolysis of neutrophils during PD-1 blockade resistance in hepatocellular carcinoma. *Nat Commun* 2024;15.

24 Chen R, Chen Q, Zheng J, et al. Serum amyloid protein A in inflammatory bowel disease: from bench to bedside. *Cell Death Discov* 2023;9:154.

25 Prass K, Meisel C, Höflich C, et al. Stroke-induced immunodeficiency promotes spontaneous bacterial infections and is mediated by sympathetic activation reversal by poststroke T helper cell type 1-like immunostimulation. *J Exp Med* 2003;198:725-36.

26 Zhu H, Hu S, Li Y, et al. Interleukins and Ischemic Stroke. *Front Immunol* 2022;13.

27 Perini F, Morra M, Alecci M, et al. Temporal profile of serum anti-inflammatory and pro-inflammatory interleukins in acute ischemic stroke patients. *Neurol Sci* 2001;22:289-96.

28 Samarakoon N, Chang T, Gunasekara V, et al. Selected serum cytokines and vitamin D levels as potential prognostic markers of acute ischemic stroke. *PLoS One* 2024;19:e0299631.

29 Liu X, Liu J, Zhao S, et al. Interleukin-4 Is Essential for Microglia/Macrophage M2 Polarization and Long-Term Recovery After Cerebral Ischemia. *Stroke* 2016;47:498-504.

30 Chen D, Li J, Huang Y, et al. Interleukin 13 promotes long-term recovery after ischemic stroke by inhibiting the activation of STAT3. *J Neuroinflammation* 2022;19:112.
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