Dataset Information

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

ABSTRACT: 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 1999 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?

SUBMITTER: Hu Y

PROVIDER: S-EPMC6916074 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature

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

Hu Yanling Y Tan Aihua A Yu Lei L Hou Chenyang C Kuang Haofa H Wu Qunying Q Su Jinghan J Zhou Qingniao Q Zhu Yuanyuan Y Zhang Chenqi C Wei Wei W Li Lianfeng L Li Weidong W Huang Yuanjie Y Huang Hongli H Xie Xing X Lu Tingxi T Zhang Haiying H Yang Xiaobo X Gao Yong Y Li Tianyu T Jiang Yonghua Y Mo Zengnan Z

BMC genomics 20191216 1

<h4>Background</h4>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.<h4>Result</h4>A total of 1999 subjects with 2 ...[more]

PMID: 31842750

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Project description:BackgroundClonorchiasis, an infectious disease caused by the liver fluke Clonorchis sinensis, may lead to the development of liver and gallbladder diseases, and even cholangiocarcinoma (CCA). However, the pathogenesis, host-pathogen interaction, and diagnostic markers for clonorchiasis remain unclear.MethodsEighteen rabbits were randomly divided into control group (n = 9) and C. sinensis-infected group (n = 9), and their plasma samples were collected at 7, 14, 28, and 63 days post-infection (dpi). Biochemical indices and metabolites in different infection periods were detected. A non-targeted ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) approach was employed to investigate the metabolic profiles of plasma in rabbits, and related metabolic pathways of differential metabolites and correlation between candidate biochemical indices and differential metabolites were analyzed. Finally, the candidate biomarkers were verified with human samples using a targeted metabolomics method.ResultsThe result of biochemical indices indicated C. sinensis infection would affect the liver function biochemical indices, especially alanine aminotransferase, aspartate transaminase (AST), glutamyl transpeptidase (GGT), total bile acid, high-density lipoprotein, and cholinesterase. The metabonomic results showed that 58, 212, 23, and 21 differential metabolites were identified in different phases of the infection. Multivariate statistical analysis of differential metabolites revealed distinct metabolic signatures during different phases of infection, with most of these signatures being observed at 14 dpi, which mainly influences the amino acid metabolisms. For metabolites and biochemical indices, AST, GGT, hypoxanthine, L-pipecolic acid, and D-glucuronate represented potential noninvasive biomarkers for the diagnosis of C. sinensis (P < 0.05 and AUC > 0.8). Furthermore, GGT and D-glucuronate levels were positively correlated with the infection (r(28) = 0.98, P < 0.0001) and showed excellent diagnostic performance (AUC = 0.972; 95% confidence interval, 0.921 to 1.000).ConclusionsThe present results provide new insights into plasma metabolic changes in rabbits during C. sinensis infection, and the potential biomarker may be used for developing an effective method to diagnose clonorchiasis in the future.

Project description:BACKGROUND: Clonorchiasis, an infectious disease caused by the liver fluke Clonorchis sinensis, may lead to the development of liver and gallbladder diseases, and even cholangiocarcinoma (CCA). However, the pathogenesis, host-pathogen interaction, and diagnostic markers for clonorchiasis remain unclear.METHODS: Eighteen rabbits were randomly divided into control group (n = 9) and C. sinensis-infected group (n = 9), and their plasma samples were collected at 7, 14, 28 and 63 days post-infection (dpi). Biochemical indices and metabolites in different infection periods were detected. A non-targeted ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) approach was employed to investigate the metabolic profiles of plasma in rabbits, and related metabolic pathways of differential metabolites and correlation between candidate biochemical indices and differential metabolites were analyzed. Finally, the candidate biomarkers were verified with human samples using a targeted metabolomics method.RESULTS: The result of biochemical indices indicated C. sinensis infection would affect the liver function biochemical indices, especially alanine aminotransferase, aspartate transaminase (AST), glutamyl transpeptidase (GGT), total bile acid, high-density lipoprotein and cholinesterase. The metabonomic results showed that 58, 212, 23 and 21 differential metabolites were identified in different phases of the infection. Multivariate statistical analysis of differential metabolites revealed distinct metabolic signatures during different phases of infection, with most of these signatures being observed at 14 dpi, which mainly influences the amino acid metabolisms. For metabolites and biochemical indices, AST, GGT, hypoxanthine, l-pipecolic acid and d-glucuronate represented potential noninvasive biomarkers for the diagnosis of C. sinensis (P < 0.05 and AUC > 0.8). Furthermore, GGT and d-glucuronate levels were positively correlated with the infection (r(28) = 0.98, P < 0.0001) and showed excellent diagnostic performance (AUC = 0.972; 95% confidence interval, 0.921 to 1.000).CONCLUSIONS: The present results provide new insights into plasma metabolic changes in rabbits during C. sinensis infection, and the potential biomarker may be used for developing an effective method to diagnose clonorchiasis in the future.

Dataset Information

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

Publications

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

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