Identification of important genes associated with total cholesterol using bioinformatics analysis.
作者信息
Mo Xing-Bo, Zhang Huan, Xu Tan, Lei Shu-Feng, Zhang Yong-Hong
机构信息
Jiangsu Key Laboratory of Preventive & Translational Medicine for Geriatric Diseases, Soochow University, 199 Renai Road, Suzhou, Jiangsu 215123, PR China.
Center for Genetic Epidemiology & Genomics, School of Public Health, Soochow University, 199 Renai Road, Suzhou, Jiangsu 215123, PR China.
出版信息
Pharmacogenomics. 2016 Feb;17(3):219-30. doi: 10.2217/pgs.15.164. Epub 2016 Jan 25.
AIM
The aim of this study was to identify related genes for total cholesterol (TC) and evaluate the functional relevance to provide evidences for prioritizing these genes.
MATERIALS & METHODS: We performed an initial gene-based association study in about 188,578 individuals. Furthermore, we performed bioinformatics analyses to support the identified genes.
RESULTS
A total of 22,098 genes were analyzed for TC levels in gene-based association analysis and 433 of them were found to be significant after Bonferroni correction (p < 2.3 × 10(-6)).
CONCLUSION
The evidence obtained from the analyses of this study signified the importance of many known genes as well as some novel genes, for example, NR1I2, STARD3 and FN1. The findings might provide more insights into the genetic basis of lipid metabolism.
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