Identification of Key Metabolites for Acute Lung Injury in Patients with Sepsis

The study aimed to detect critical metabolites in acute lung injury (ALI). A comparative analysis of microarray profile of patients with sepsis-induced ALI compared with sepsis patients with was conducted using bioinformatic tools through constructing multi-omics network. Multi-omics composite networks (gene network, metabolite network, phenotype network, gene-metabolite associa-tion network, phenotype-gene association network, and phenotype-metabolite association network) were con-structed, following by integration of these composite networks to establish a heterogeneous network. Next, seed genes, and ALI phenotype were mapped into the heterogeneous network to further obtain a weighted composite network. Random walk with restart (RWR) was used for the weighted composite network to extract and prioritize the metabolites. On the basis of the distance proximity among metabolites, the top 50 metabo-lites with the highest proximity were identified, and the top 100 co-expressed genes interacted with the top 50 metabolites were also screened out. Totally, there were 9363 nodes and 10,226,148 edges in the integrated composite network. There were 4 metabolites with the scores > 0.009, including CHITIN, Tretinoin, sodium ion, and Celebrex. Adenosine 5'-diphosphate, triphosadenine, and tretinoin had higher degrees in the composite network and the co-expressed network. Adenosine 5'-diphosphate, triphosadenine, and tretinoin may be potential biomarkers for diagno-sis and treatment of ALI.