Combined metabolic, phenomic and genomic data to prioritize atrial fibrillation-related metabolites

Yan,Zhi-Tao; Huang,Jin-Mei; Luo,Wen-Li; Liu,Ji-Wen; Zhou,Kang

doi:10.3892/etm.2019.7443

Combined metabolic, phenomic and genomic data to prioritize atrial fibrillation-related metabolites

Authors:
- Zhi-Tao Yan
- Jin-Mei Huang
- Wen-Li Luo
- Ji-Wen Liu
- Kang Zhou
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Affiliations: Department of Cardiology, The First Affiliated Hospital of the Medical College, Shihezi University, Shihezi, Xinjiang 832000, P.R. China, Department of General Surgery, The First Affiliated Hospital of the Medical College, Shihezi University, Shihezi, Xinjiang 832000, P.R. China, Department of Gerontology, The First Affiliated Hospital of the Medical College, Shihezi University, Shihezi, Xinjiang 832000, P.R. China, Department of Internal Medicine, Affiliated Midong Hospital of the People's Hospital of Xinjiang Uygur Autonomous Region, Urumqi, Xinjiang 830000, P.R. China
Published online on: March 26, 2019 https://doi.org/10.3892/etm.2019.7443
Pages: 3929-3934

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Abstract

Metabolites in atrial fibrillation (AF) were characterized to further explore the molecular mechanisms of AF by integrating metabolic, phenomic and genomic data. Gene expression data on AF (E-GEOD-79768) were downloaded from the EMBL-EBI database, followed by identification of differentially expressed genes (DEGs) which were used to construct gene-gene network. Then, multi-omics composite networks were constructed. Subsequently, random walk with restart was expanded to a multi-omics composite network to identify and prioritize the metabolites according to the AF-related seed genes deposited in the OMIM database, the whole metabolome as candidates and the phenotype of AF. Using the interaction score among metabolites, we extracted the top 50 metabolites, and identified the top 100 co-expressed genes interacted with the top 50 metabolites. Based on the FDR <0.05, 622 DEGs were extracted. In order to demonstrate the intrinsic mode of this method, we sorted the metabolites of the composite network in descending order based on the interaction scores. The top 5 metabolites were respectively weighed potassium, sodium ion, chitin, benzo[a]pyrene-7,8-dihydrodiol-9,10-oxide, and celebrex (TN). Potassium and sodium ion possessed higher degrees in the subnetwork of the entire composite network and the co-expressed network. Metabolites such as potassium and sodium ion may provide valuable clues for early diagnostic and therapeutic targets for AF.

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