@ARTICLE{10.3389/fcell.2020.00453, AUTHOR={Li, Xiaoying and Shi, Weilin and Zhang, Ruyou and Zhang, Shuang and Hou, Wenying and Wu, Yingnan and Lu, Rui and Feng, Yanan and Tian, Jiawei and Sun, Litao}, TITLE={Integrate Molecular Phenome and Polygenic Interaction to Detect the Genetic Risk of Ischemic Stroke}, JOURNAL={Frontiers in Cell and Developmental Biology}, VOLUME={8}, YEAR={2020}, URL={https://www.frontiersin.org/articles/10.3389/fcell.2020.00453}, DOI={10.3389/fcell.2020.00453}, ISSN={2296-634X}, ABSTRACT={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.} }