Flow cytometry-based peripheral blood analysis as an easily friendly tool for prognostic monitoring of acute ischemic stroke: a multicenter study

• Published in: Frontiers in immunology Vol. 15; p. 1402724
• Main Authors: Lu, Kang, Ni, Wanmao, Yue, Juanqing, Cheng, Yongran, Du, Jing, Li, Yanchun, Tong, Xiangmin, Chen, Guo-Bo, Wang, Ying
• Format: Journal Article
• Language: English
• Published: Switzerland Frontiers Media S.A 21.05.2024
• Subjects: acute ischemic stroke; Aged; Aged, 80 and over; Biomarkers - blood; Female; Flow Cytometry - methods; Humans; Immunology; immunophenotypic indicators; Immunophenotyping; Ischemic Stroke - blood; Ischemic Stroke - diagnosis; Ischemic Stroke - immunology; Ischemic Stroke - mortality; LASSO; Male; Middle Aged; Prognosis; prognostic model; Prospective Studies; survival; immunophenotypic indicators; prognostic model; acute ischemic stroke; LASSO; survival
• ISSN: 1664-3224; 1664-3224
• DOI: 10.3389/fimmu.2024.1402724

Acute ischemic stroke (AIS) is a leading cause of mortality, severe neurological and long-term disability world-wide. Blood-based indicators may provide valuable information on identified prognostic factors. However, currently, there is still a lack of peripheral blood indicators for the prognosis of AIS. We aimed to identify the most promising prognostic indicators and establish prognostic models for AIS. 484 subjects enrolled from four centers were analyzed immunophenotypic indicators of peripheral blood by flow cytometry. Least absolute shrinkage and selection operator (LASSO) regression was applied to minimize the potential collinearity and over-fitting of variables measured from the same subject and over-fitting of variables. Univariate and multivariable Cox survival analysis of differences between and within cohorts was performed by log-rank test. The areas under the receiving operating characteristic (ROC) curves were used to evaluate the selection accuracy of immunophenotypic indicators in identifying AIS subjects with survival risk. The prognostic model was constructed using a multivariate Cox model, consisting of 402 subjects as a training cohort and 82 subjects as a testing cohort. In the prospective study, 7 immunophenotypic indicators of distinct significance were screened out of 72 peripheral blood immunophenotypic indicators by LASSO. In multivariate cox regression, CTL (%) [HR: 1.18, 95% CI: 1.03-1.33], monocytes/μl [HR: 1.13, 95% CI: 1.05-1.21], non-classical monocytes/μl [HR: 1.09, 95% CI: 1.02-1.16] and CD56 NK cells/μl [HR: 1.13, 95% CI: 1.05-1.21] were detected to decrease the survival probability of AIS, while Tregs/μl [HR:0.97, 95% CI: 0.95-0.99, p=0.004], B /μl [HR:0.90, 95% CI: 0.85-0.95, p=0.023] and CD16 NK cells/μl [HR:0.93, 95% CI: 0.88-0.98, p=0.034] may have the protective effect. As for indicators' discriminative ability, the AUC for CD56 NK cells/μl attained the highest of 0.912. In stratification analysis, the survival probability for AIS subjects with a higher level of Tregs/μl, B /μl, CD16 NK cells/μl, or lower levels of CD56 NK cells/μl, CTL (%), non-classical monocytes/μl, Monocytes/μl were more likely to survive after AIS. The multivariate Cox model showed an area under the curve (AUC) of 0.805, 0.781 and 0.819 and 0.961, 0.924 and 0.982 in the training and testing cohort, respectively. Our study identified 7 immunophenotypic indicators in peripheral blood may have great clinical significance in monitoring the prognosis of AIS and provide a convenient and valuable predictive model for AIS.