预测中风发生风险的潜在关键基因:一种计算方法

Gourab Das , Pradeep Kumar
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引用次数: 0

摘要

探讨与脑卒中分型及亚型发病及预后相关的前瞻性关键基因及通路。通过NCBI基因数据库(https://www.ncbi.nlm.nih.gov/gene)对人类基因进行基因组组装,构建38个patch release 13个已知基因符号。使用笔划相关关键词构建PubMed高级查询,并使用每个基因符号与查询之间的归一化点互信息(nPMI)计算关联。在其类型和亚型中研究与中风风险相关的基因,以发现遗传标记来预测具有其亚型的中风风险的个体。共有2785个(9.4%)基因被发现与中风风险有关。根据脑卒中类型,分别有1287个(46.2%)和376个(13.5%)基因与缺血性脑卒中(IS)和出血性脑卒中(HS)相关。基于TOAST分类的IS进一步分层,86个(6.6%)基因局限于大动脉粥样硬化;131个(10.1%)和130个(10%)基因与IS亚型小血管疾病和心脏栓塞的风险相关。通过已发表的meta分析和GWAS研究报告的证据表明,9个高度相关的基因存在相关性,因此,我们得出结论,由CYP4A11、ALOX5P、NOTCH、NINJ2、FGB、MTHFR、PDE4D、HDAC9和ZHFX3组成的9个基因组成的预后面板可以作为预测个体发生卒中风险的诊断标志物。这九种预后标志物的验证需要通过进行大样本量的病例对照研究来进一步进行。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Potential key genes for predicting risk of stroke occurrence: A computational approach

To investigate prospective key genes and pathways associated with the pathogenesis and prognosis of stroke types along with subtypes. Human genes using genome assembly build 38 patch release 13 with known gene symbols through NCBI gene database (https://www.ncbi.nlm.nih.gov/gene) were fetched. PubMed advanced queries were constructed using stroke-related keywords and associations were calculated using Normalized pointwise mutual information (nPMI) between each gene symbol and queries. Genes related with stroke risk within their types and subtypes were investigated in order to discover genetic markers to predict individuals who are at the risk of developing stroke with their subtypes. A total of 2,785 (9.4%) genes were found to be linked to the risk of stroke. Based on stroke types, 1,287 (46.2%) and 376 (13.5%) genes were found to be related with ischemic stroke (IS) and hemorrhagic stroke (HS) respectively. Further stratification of IS based on TOAST classification, 86 (6.6%) genes were confined to Large artery atherosclerosis; 131 (10.1%) and 130 (10%) genes were related with the risk of small vessel disease and Cardioembolism subtypes of IS. Evidences reported through published meta-analysis and GWAS studies suggested for the association of nine highly associated genes and therefore, we concluded a prognostic panel of nine genes comprising of CYP4A11, ALOX5P, NOTCH, NINJ2, FGB, MTHFR, PDE4D, HDAC9, and ZHFX3 can be treated as a diagnostic marker to predict individuals who are at the risk of developing stroke. Validation of these nine prognostic markers are further required by conducting case-control studies embedded with large sample size.

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来源期刊
Neuroscience informatics
Neuroscience informatics Surgery, Radiology and Imaging, Information Systems, Neurology, Artificial Intelligence, Computer Science Applications, Signal Processing, Critical Care and Intensive Care Medicine, Health Informatics, Clinical Neurology, Pathology and Medical Technology
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