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  • 统计与管理学院2018年学术报告第28期

    【主 题】 Post-GWAS Secondary Phenotype Analysis is Cost-Benefit Only with Valid Analytical Approach

    【报告人】 康国莲  Associate Member

    St. Jude Children’s Research Hospital

    【时 间】 2018年06月29日(星期五)10:00-11:00

    【地 点】 上海财经大学统计与管理学院大楼1208会议室

    摘 要】Genome-wide association studies (GWAS) have been successful in the last decades to identify common variants associated with common or rare diseases. Study designs most commonly used for GWAS are based on a primary outcome including the case-control study (CC) for studying a common disease or extreme phenotype sequencing design (EPS) for studying an ordinal or continuous phenotype, such as the well-known National Heart, Lung, and Blood Institute Exome Sequencing Project. Besides the primary outcome, extensive data on secondary phenotypes (SP) that may correlate and share the common genetic variants with the primary outcomes are available. Although naïve methods for GWAS could be applied to analyze the secondary phenotypes, they lead to biased risk estimates if there is correlation between the primary outcome and secondary phenotype. This is resulted from the fact that the GWAS samples selected are not a random representative sample of the secondary outcome. Thus, the critical question is how to analyze these secondary outcomes in post-GWAS era? Here, two novel statistical methods for CC (STcc) and EPS (STEPS) designs are proposed. Extensive simulation studies show that the two methods can control false positive rate well and have larger power compared to naïve methods, which is robust to effect pattern of the genetic variant (risk or protective), rare or common variants, and trait distributions). To show their cost-benefit, we also mimicked to re-design two new retrospective studies as in the real practice based on primary outcome of interest, which is same as SP in the EPS study. Application to a genome-wide association study of Benign Ethnic Neutropenia with 7 SPs under an EPS design also demonstrates the striking superiority of the proposed two methods over their alternatives.

    嘉宾简介】康国莲博士,一直从事统计遗传、系统生物学、临床实验、和遗传流行病研究。已发表SCI学术论文70多篇,其中包括Nature Genetics, Journal of Clinical Oncology等,被独立引用800次以上。其多个研究成果被世界著名媒体报道(美国: NewsRX.com 和ScienceDaily, 委内瑞拉: International Adaptogens,英国Nature Review Genetics))并被收录于书《Transgénicos》 (古巴)。 主持1项由美国NHLBI资助的高水平科研项目的Data Coordinating Center; 9项由美国NCI, NIH资助的科研项目的leader biostatistician. 设计了多于50多个临床试验protocol. 参与评审NIH(USA)和DPFS(UK)项目,是多个国际期刊的编委。