Tissue Kallikrein as a Mediator in Stroke Outcomes among Patients With Metabolic Syndrome: A Multicenter Study Integrating Big Data and Biomarkers

Abstract

Metabolic syndrome (MetS) poses a significant risk to the cerebrovascular system, impacting the prognosis of stroke patients. This study investigated the link between MetS and stroke-related outcomes, exploring tissue kallikrein 1 (KLK1) as a potential mediator. In the derivation cohort, a total of 17,106 stroke-diagnosed patients were assessed, with 6917 individuals (40.4%) presenting comorbid MetS. Multifactorial analysis identified stroke concurrent with MetS (adjusted odds ratio = 1.42; 95% confidence interval: 1.17–1.72; p < 0.001) as a risk factor for unfavorable outcomes among stroke patients. Further bioinformatics analyses indicated that obesity, diabetes, and hypertension were associated with reduced KLK1 levels (all p < 0.05). In the validation cohort, 1268 first-ever stroke patients were enrolled, confirming a higher incidence of adverse outcomes in those with MetS, compared with those without (223 (28.1%) vs. 167 (35.2%); p < 0.01). Stroke patients with MetS, exhibited lower KLK1 levels (16.8 ± 6.52 vs. 15.6 ± 6.3; p < 0.01). Mediation analyses supported that MetS contributed to adverse outcomes through the mediating effect of decreased KLK1 levels (p < 0.05). This study highlights the risk of MetS in stroke patients and suggests a potential role for KLK1 as a mediating factor.

Keywords

big data / bioinformatic / KLK1 / machine learning / metabolic syndrome / observational studies / stroke

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