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On May 29, "European Journal of Human Genetics" published online the research results of Xu Shuhua's research group of the Institute of Computational Biology, Shanghai Academy of Biological Sciences "A panel of ancestry informative markers to estimate and correct potential effects of population stratification in Han Chinese" . This work addresses the problem of false positive results due to population genetic structure (or population stratification) in complex disease association studies, and establishes a set of genetic markers that identify the internal genetic structure of the Han population and control population stratification in association analysis of complex diseases. This set of markers is particularly suitable for association studies based on candidate gene strategies in the "post-GWAS" era.
Association analysis is an important means to study the genetic influencing factors of complex diseases and establish a "phenotype-genotype" relationship. Association studies based on population sample design, especially association studies based on "case-control" design, often face a difficulty is the false positive results caused by population genetic structure or population stratification as a serious confounding factor. The Han people have a long history and complex origins. In addition, thousands of years of gene exchange and ethnic fusion have made the genetic composition of the Han people extremely complicated. In the early study of Xu Shuhua, the genetic structure inside the Han population has been found, and often leads to false positive results in the association analysis of the Han population. Therefore, how to identify and control the influence of population genetic structure on the results of association analysis has become an unavoidable problem in the study of gene mapping of complex diseases.
This study established DNA markers that can highly identify the genetic structure of the Han population by screening the whole genome data of 5,500 Han individuals, and further evaluated the effectiveness of this set of markers through experimental data and computer simulation. The research results have practical application value for the future research on association analysis among the Han population. Through this set of markers, the direct identification of genetic structure based on DNA information and the objective classification and screening of samples are the prerequisites for rational experimental design of association analysis and the necessary conditions for ensuring the reliability of association analysis results.
This work was carried out in collaboration with Professor Xu Shuhua of the Institute of Computational Biology, Professor Yongyong Shi of Shanghai Jiaotong University and Professor Jin Li of Fudan University. Qin Pengfei, a doctoral student of the Institute of Computational Biology, etc., carried out specific analysis. The research work was supported by funds from the National Natural Science Foundation of China, the Chinese Academy of Sciences, the Shanghai Municipal Science and Technology Commission, the German Max Planck Society, and the Hong Kong Wang Kuancheng Education Foundation.
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