Prioritization of candidate metabolites for postmenopausal osteoporosis using multi-omics composite network.

Risk metabolites of postmenopausal osteoporosis (PO) were explored to offer a theoretical basis for future therapy. The data E-GEOD-7429 were downloaded from ArrayExpress database. In total 20 samples deprived from postmenopausal women having low or high bone mineral density (BMD) were covered in this expression profile. After screening of differentially expressed genes (DEGs), gene-gene network was constructed taking the intersection between the DEGs and genes in the seed protein-protein interaction network. Then, the other five networks were established, including metabolite, phenotype, gene-metabolite, phenotype-gene, and phenotype-metabolite networks. Next, these 6 networks were integrated into one weighted multi-omics network to further identify the candidate metabolites using random walk with restart based on the PO-related seed genes, seed metabolites and phenotype. Using the score among nodes of the weighted composite network, the top 50 metabolites, and the top 100 co-expressed genes interacting with the top 50 metabolites were detected. A set of 601 DEGs between low BMD and high BMD samples were selected. Significantly, the top 5 metabolites were respectively glucosylgalactosyl hydroxylysine, all-trans-5,6-epoxyretinoic acid, tretinoin, colecalciferol, and rocaltrol. Moreover, 3 metabolites (estraderm, triphosadenine, and tretinoin) had a degree >50 in the co-expression network. Tretinoin was the member of the top 5 metabolites, and estraderm was a metabolite with the seventh interaction score. A series of metabolites, tretinoin and estraderm might be closely associated with the onset and progression of PO.