Inflammation‐Derived and Clinical Indicator‐Based Predictive Model for Ischemic Stroke Recovery

作者：Jiao Luo, You Cai, Peng Xiao, Changchun Cao, Mei‐Ling Huang, Xiaohua Zhang, Guo Jie, Yongyang Huo, Qiaoyan Tang, Liuyang Zhao, Jiabang Liu, Yaqi Ma, Anqun Yang, Mingchao Zhou, Yulong Wang · 发表于：Journal of the American Heart Association · 年份：2024 · DOI：10.1161/jaha.124.035609 · 被引用次数：7 · 研究领域：Neuroinflammation and Neurodegeneration Mechanisms、S100 Proteins and Annexins、Acute Ischemic Stroke Management

BACKGROUND: Neuroinflammatory responses are closely associated with poststroke prognosis severity. This study aimed to develop a predictive model, combining inflammation-derived markers and clinical indicators, for distinguishing functional outcomes in patients with subacute ischemic stroke. METHODS AND RESULTS: Based on activities of daily living assessments, ischemic stroke participants were categorized into groups with little effective (LE) recovery and obvious effective (OE) recovery. Initial biocandidates were identified by overlapping differentially expressed proteins from proteomics of clinical serum samples (5 LE, 5 OE, and 6 healthy controls) and differentially expressed genes from an RNA sequence of the ischemic cortex in middle cerebral artery occlusion mice (n=3). Multidimensional validations were conducted in ischemia-reperfusion models and a clinical cohort (15 LE, 11 OE, and 18 healthy controls). Models of robust biocandidates combined with clinical indicators were developed with machine learning in the training data set and prediction in another test data set (15 LE and 11 OE). We identified 194 differentially expressed proteins (LE versus healthy controls) and 174 differentially expressed proteins (OE versus healthy controls) in human serum, and 5121 differentially expressed genes (day 3) and 5906 differentially expressed genes (day 7) in middle cerebral artery occlusion mice cortex. Inflammation-derived biomarkers TIMP1 (tissue inhibitor metalloproteinase-1)...