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

Biomarkers Functional outcome Stroke Stroke severity

Journal

Neurological research and practice
ISSN: 2524-3489
Titre abrégé: Neurol Res Pract
Pays: England
ID NLM: 101767802

Informations de publication

Date de publication:
20 Jul 2023
Historique:
received: 04 04 2023
accepted: 20 06 2023
medline: 20 7 2023
pubmed: 20 7 2023
entrez: 19 7 2023
Statut: epublish

Résumé

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. 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. 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], p 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.

Sections du résumé

BACKGROUND 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 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 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], p
CONCLUSIONS 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.

Identifiants

pubmed: 37468969
doi: 10.1186/s42466-023-00259-3
pii: 10.1186/s42466-023-00259-3
pmc: PMC10357843
doi:

Types de publication

Journal Article

Langues

eng

Pagination

31

Informations de copyright

© 2023. The Author(s).

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Auteurs

Lino Braadt (L)

Department of Neurology and Clinical Neurophysiology, University Hospital Augsburg, Augsburg, Germany. lino-dominic.braadt@uk-augsburg.de.

Markus Naumann (M)

Department of Neurology and Clinical Neurophysiology, University Hospital Augsburg, Augsburg, Germany.

Dennis Freuer (D)

Epidemiology, Faculty of Medicine, University of Augsburg, Augsburg, Germany.

Timo Schmitz (T)

Epidemiology, Faculty of Medicine, University of Augsburg, Augsburg, Germany.

Jakob Linseisen (J)

Epidemiology, Faculty of Medicine, University of Augsburg, Augsburg, Germany.

Michael Ertl (M)

Department of Neurology and Clinical Neurophysiology, University Hospital Augsburg, Augsburg, Germany.

Classifications MeSH