A phenomics-based approach for the detection and interpretation of shared genetic influences on 29 biochemical indices in southern Chinese men

• Published in: BMC Genomics
• Main Authors: Hu, Yanling, Tan, Aihua, Yu, Lei, Hou, Chenyang, kuang, haofa, Wu, Qunying, sun, Jinghan, zhou, Qingniao, Zhu, Yuanyuan, Zhang, Chenqi, Wei, Wei, li, Lianfeng, Li, Weidong, Huang, Yuanjie, Huang, Hongli, Xie, Xing, Lu, Tingxi, Zhang, Haiying, Yang, Xiaobo, Gao, Yong, Li, Tianyu, Jiang, yonghua, mo, zengnan
• Format: Web Resource
• Language: English
• Published: Durham Research Square 03.12.2019
• Subjects: Genetics; Metabolism
• DOI: 10.21203/rs.2.12060/v5

Background: Phenomics provides new technologies and platforms as a systematic phenome-genome approach. However, few studies have reported on the systematic mining of shared genetics among clinical biochemical indices based on phenomics methods, especially in China. This study aimed to apply phenomics to systematically explore shared genetics among 29 biochemical indices based on the Fangchenggang Area Male Health and Examination Survey cohort. Result: A total of 1,999 subjects with 29 biochemical indices and 709,211 single nucleotide polymorphisms (SNPs) were subjected to phenomics analysis. Three bioinformatics methods, namely, Pearson’s test, Jaccard’s index, and linkage disequilibrium score regression, were used. The results showed that 29 biochemical indices were from a network. IgA, IgG, IgE, IgM, HCY, AFP and B12 were in the central community of 29 biochemical indices. Key genes and loci associated with metabolism traits were further identified, and shared genetics analysis showed that 29 SNPs (P < 10-4) were associated with three or more traits. After integrating the SNPs related to two or more traits with the GWAS catalogue, 31 SNPs were found to be associated with several diseases (P < 10-8). Using ALDH2 as an example to preliminarily explore its biological function, we also confirmed that the rs671 (ALDH2) polymorphism affected multiple traits of osteogenesis and adipogenesis differentiation in 3T3-L1 preadipocytes. Conclusion: All these findings indicated a network of shared genetics and 29 biochemical indices, which will help fully understand the genetics participating in biochemical metabolism.