Integrate Molecular Phenome and Polygenic Interaction to Detect the Genetic Risk of Ischemic Stroke
Integrate Molecular Phenome and Polygenic Interaction to Detect the Genetic Risk of Ischemic Stroke
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整合分子表型和多基因相互作用来检测缺血性中风的遗传风险
DOI：
10.3389/fcell.2020.00453
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发表时间：
2020-06-24
影响因子：
5.5
通讯作者：
Sun, Litao
中科院分区：
文献类型：
--
作者：
Li, Xiaoying;Shi, Weilin;Sun, Litao
缺血性卒中(IS)是导致人类死亡的主要原因之一，通过单核苷酸多态性(SNP)与表型关系的关联研究，不断计算和检测其遗传风险。然而，对IS风险的系统评估仍需要从组学水平上积累分子表型和功能。在本研究中，我们结合表型组、多基因互作基因表达和分子功能来筛选危险基因和分子功能。然后，我们进行了病例对照研究，包括507例病例和503名对照，以验证候选功能基因与中国北方汉族人群IS表型之间的遗传关联关系。中介分析表明，血压、高密度脂蛋白和葡萄糖介导了SOCS1、CD137、ALOX5AP、RNLS和KALRN在IS中的潜在作用，这既是功能分析，也是基因关联。采用多因素降维(MDR)方法对SNP-SNP的交互作用进行分析时，也呈现出IS风险的组合效应。进一步的相互作用网络和基因本体论(GO)丰富分析表明，CD137和KALRN在炎症反应中的作用可能在IS的发病和发展中发挥更大的作用。本研究通过整合多种组学信息，开辟了一条评价IS潜在机制和生物标志物的新途径。
Ischemic stroke (IS) is one of the leading causes of death, and the genetic risk of which are continuously calculated and detected by association study of single nucleotide polymorphism (SNP) and the phenotype relations. However, the systematic assessment of IS risk still needs the accumulation of molecular phenotype and function from the level of omics. In this study, we integrated IS phenome, polygenic interaction gene expression and molecular function to screen the risk gene and molecular function. Then, we performed a case-control study including 507 cases and 503 controls to verify the genetic associated relationship among the candidate functional genes and the IS phenotype in a northern Chinese Han population. Mediation analysis revealed that the blood pressure, high density lipoprotein (HDL) and glucose mediated the potential effect of SOCS1, CD137, ALOX5AP, RNLS, and KALRN in IS, both for the functional analysis and genetic association. And the SNP-SNP interactions analysis by multifactor dimensionality reduction (MDR) approach also presented a combination effect of IS risk. The further interaction network and gene ontology (GO) enrichment analysis suggested that CD137 and KALRN functioning in inflammatory could play an expanded role during the pathogenesis and progression of IS. The present study opens a new avenue to evaluate the underlying mechanisms and biomarkers of IS through integrating multiple omics information.