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

Abstract

Background:The study aimed to detect critical metabolites in acute lung injury (ALI). Methods: 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. Multiomics composite networks (gene network, metabolite network, phenotype network, gene-metabolite association network, phenotype-gene association network, and phenotype-metabolite association network) were constructed, 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 metabolites with the highest proximity were identified, and the top 100 co-expressed genes interacted with the top 50 metabolites were also screened out. Results: 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. Conclusion: Adenosine 5'-diphosphate, triphosadenine, and tretinoin may be potential biomarkers for diagnosis and treatment of ALI.

Comprehensive Analysis Strategy of Nervous–Endocrine–Immune-Related Metabolites to Evaluate Arachidonic Acid as a Novel Diagnostic Biomarker in Depression

“…Metabolites and metabolites are related, usually in the form of a network, called the metabolite–metabolite interaction (MMI) network. At present, MMI network analysis is used in atherosclerosis, acute lung injury, and other aspects to explore important molecular mechanisms. , Therefore, through this new technology, we can clarify the disease mechanism from a holistic perspective.…”

“…At present, MMI network analysis is used in atherosclerosis, acute lung injury, and other aspects to explore important molecular mechanisms. 14,15 Therefore, through this new technology, we can clarify the disease mechanism from a holistic perspective. This study aims to select the NEI-related depression metabolites from metabolomics based on the network visualization and functional analysis.…”