人口分层
虚假关系
遗传关联
单核苷酸多态性
人口
基因分型
全基因组关联研究
生物
遗传学
队列
基因型
计算机科学
医学
统计
环境卫生
机器学习
数学
基因
作者
Lon R. Cardon,Lyle J. Palmer
出处
期刊:The Lancet
[Elsevier BV]
日期:2003-02-01
卷期号:361 (9357): 598-604
被引量:1129
标识
DOI:10.1016/s0140-6736(03)12520-2
摘要
Summary
Great efforts and expense have been expended in attempts to detect genetic polymorphisms contributing to susceptibility to complex human disease. Concomitantly, technology for detection and scoring of single nucleotide polymorphisms (SNPs) has undergone rapid development, extensive catalogues of SNPs across the genome have been constructed, and SNPs have been increasingly used as a means for investigation of the genetic causes of complex human diseases. For many diseases, population-based studies of unrelated individuals—in which case-control and cohort studies serve as standard designs for genetic association analysis—can be the most practical and powerful approach. However, extensive debate has arisen about optimum study design, and considerable concern has been expressed that these approaches are prone to population stratification, which can lead to biased or spurious results. Over the past decade, a great shift has been noted, away from case-control and cohort studies, towards family-based association designs. These designs have fewer problems with population stratification but have greater genotyping and sampling requirements, and data can be difficult or impossible to gather. We discuss past evidence for population stratification on genotype-phenotype association studies, review methods to detect and account for it, and present suggestions for future study design and analysis.
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