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    The prevalence of intracranial aneurysm (IA) is increasing, and the consequences of its rupture are severe. This study aimed to reveal specific, sensitive, and non-invasive biomarkers for diagnosis and classification of ruptured and unruptured IA, to benefit the development of novel treatment strategies and therapeutics altering the course of the disease. We first assembled an extensive candidate biomarker bank of IA, comprising up to 717 proteins, based on altered proteins discovered in the current tissue and serum proteomic analysis, as well as from previous studies. Mass spectrometry assays for hundreds of biomarkers were efficiently designed using our proposed deep learning-based method, termed DeepPRM. A total of 113 potential markers were further quantitated in serum cohort I (n = 212) & II (n = 32). Combined with a machine-learning-based pipeline, we built two sets of biomarker combinations (P6 & P8) to accurately distinguish IA from healthy controls (accuracy: 87.50%) or classify IA rupture patients (accuracy: 91.67%) upon evaluation in the external validation set (n = 32). This extensive circulating biomarker development study provides valuable knowledge about IA biomarkers. © 2022 The Authors. Published under the terms of the CC BY 4.0 license.

    Citation

    Yueting Xiong, Yongtao Zheng, Yan Yan, Jun Yao, Hebin Liu, Fenglin Shen, Siyuan Kong, Shuang Yang, Guoquan Yan, Huanhuan Zhao, Xinwen Zhou, Jia Hu, Bin Zhou, Tao Jin, Huali Shen, Bing Leng, Pengyuan Yang, Xiaohui Liu. Circulating proteomic panels for risk stratification of intracranial aneurysm and its rupture. EMBO molecular medicine. 2022 Feb 07;14(2):e14713

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    PMID: 34978375

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