学术报告-Guimin Gao

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2018-06-20 08:41:00

学术报告

    题      目:Trans-ethnic Predicted Expression Genome-wide Association Analysis Identifies a Gene for Estrogen Receptor-negative Breast Cancer

报  告  人:Guimin Gao 副教授  (邀请人:金华)

                     美国芝加哥大学


时      间:2018-06-20 16:00--17:00

地      点:学院401

报告人简介:

      现任美国芝加哥大学公共卫生系副教授。主要研究方向:统计遗传学和生物信息学。曾任亚拉巴马大学助理教授、弗吉尼亚州立邦联大学生物统计系副教授;已在国际发表SCI论文20余篇,并获得美国多项科研经费。


摘      要:

   Genome-wide association studies (GWAS) have identified more than 90 susceptibility loci for breast cancer, but the underlying biology of those associations needs to be further elucidated. More genetic factors for breast cancer are yet to be identified but sample size constraints preclude the identification of individual genetic variants with weak effects using traditional GWAS methods. To address this complexity challenge, we utilized a gene-
level expression-based method, implemented in the MetaXcan software, to infer predict gene expression levels of for 11,536 genes using expression quantitative trait loci and examine the genetically-predicted expression of specific genes for association with overall breast cancer risk and estrogen receptor (ER)-negative breast cancer risk. This study demonstrated that expression-based gene mapping is a promising approach for identifying cancer susceptibility genes.