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. 2023 Jul 20;5(1):31.
doi: 10.1186/s42466-023-00259-3.

Novel inflammatory biomarkers associated with stroke severity: results from a cross-sectional stroke cohort study

Lino Braadt  1 , Markus Naumann  2 , Dennis Freuer  3 , Timo Schmitz  3 , Jakob Linseisen #  3 , Michael Ertl #  2
Affiliations

Novel inflammatory biomarkers associated with stroke severity: results from a cross-sectional stroke cohort study

Lino Braadt et al. Neurol Res Pract. .

Abstract

Background: Stroke is a leading cause of mortality and disability worldwide and its occurrence is expected to increase in the future. Blood biomarkers have proven their usefulness in identification and monitoring of the disease. Stroke severity is a major factor for estimation of prognosis and risk of recurrent events, but knowledge on respective blood biomarkers is still scarce. Stroke pathophysiology comprises a multitude of ischemia-induced inflammatory and immune mediated responses. Therefore, the assessment of an immune-related panel in correlation with stroke severity seems promising.

Methods: In the present cross-sectional evaluation, a set of 92 blood biomarkers of a standardized immune panel were gathered (median 4.6 days after admission) and related to stroke severity measures, assessed at hospital admission of acute stroke patients. Multivariable logistic regression models were used to determine associations between biomarkers and modified Rankin Scale (mRS), linear regression models were used for associations with National Institute of Health Stroke Scale.

Results: 415 patients (mean age 69 years; 41% female) were included for biomarker analysis. C-type lectin domain family 4 member G (CLEC4G; OR = 2.89, 95% CI [1.49; 5.59], padj = 0.026, Cytoskeleton-associated protein 4 (CKAP4; OR = 2.38, 95% CI [1.43; 3.98], padj = 0.019), and Interleukin-6 (IL-6) (IL6; OR = 1.97, 95% CI [1.49; 2.62], padj < 0.001) were positively associated with stroke severity measured by mRS, while Lymphocyte antigen 75 (LY75; OR = 0.37, 95% CI [0.19; 0.73], padj = 0.049) and Integrin alpha-11 (ITGA11 OR = 0.24, 95% CI [0.14, 0.40] padj < 0.001) were inversely associated. When investigating the relationships with the NIHSS, IL-6 (β = 0.23, 95% CI [0.12, 0.33] padj = 0.001) and ITGA11 (β = - 0.60, 95% CI [- 0.83, - 0.37] padj < 0.001) were significantly associated.

Conclusions: Higher relative concentrations of plasma CLEC4G, CKAP4, and IL-6 were associated with higher stroke severity, whereas LY75 and ITGA11 showed an inverse association. Future research might show a possible use as therapeutic targets and application in individual risk assessments.

Keywords: Biomarkers; Functional outcome; Stroke; Stroke severity.

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Conflict of interest statement

The authors declared that they have no competing interests.

Figures

Fig. 1
Fig. 1
Consort chart of patient enrolment and analysis
Fig. 2
Fig. 2
Odds ratios and 95% confidence intervals for the association between immune biomarkers and mRS (0–2 versus > 2). Presented p values are FDR-adjusted. Arrows represent confidence intervals exceeding the plotted x-range
Fig. 3
Fig. 3
Relative plasma biomarker concentrations by mRS group (* outliers +/− 3 * IQR)
Fig. 4
Fig. 4
β estimates and 95% confidence intervals for the association between immune biomarkers and the square root transformed NIHSS. Presented p values are FDR-adjusted
See this image and copyright information in PMC

References

    1. Seners P, Ben Hassen W, Lapergue B, Arquizan C, Heldner MR, Henon H, et al. Prediction of early neurological deterioration in individuals with minor stroke and large vessel occlusion intended for intravenous thrombolysis alone. JAMA Neurology. 2021;78(3):321–328. doi: 10.1001/jamaneurol.2020.4557. - DOI - PMC - PubMed
    1. Kolmos M, Christoffersen L, Kruuse C. Recurrent ischemic stroke—A systematic review and meta-analysis. Journal of Stroke and Cerebrovascular Diseases. 2021;30(8):105935. doi: 10.1016/j.jstrokecerebrovasdis.2021.105935. - DOI - PubMed
    1. Wardlaw JM, Brazzelli M, Chappell FM, Miranda H, Shuler K, Sandercock PA, et al. ABCD2 score and secondary stroke prevention: Meta-analysis and effect per 1,000 patients triaged. Neurology. 2015;85(4):373–380. doi: 10.1212/WNL.0000000000001780. - DOI - PMC - PubMed
    1. Stinear CM, Byblow WD, Ackerley SJ, Barber PA, Smith MC. Predicting recovery potential for individual stroke patients increases rehabilitation efficiency. Stroke. 2017;48(4):1011–1019. doi: 10.1161/STROKEAHA.116.015790. - DOI - PubMed
    1. Heo J, Yoon JG, Park H, Kim YD, Nam HS, Heo JH. Machine learning-based model for prediction of outcomes in acute stroke. Stroke. 2019;50(5):1263–1265. doi: 10.1161/STROKEAHA.118.024293. - DOI - PubMed

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