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. Multi-omics 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.
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33. Huang R, Tian Z, Wu H (2015). Quercetin protects against lipopolysaccharide-induced acute lung injury in rats through suppression of inflammation and oxidative stress. Arch Med Sci, 11: 427-432.
34. Raja SB, Najoua M, Anouar A et al (2014). Protective Effect of ATRA on Bleomycin Induced Lung Fibrosis in Rat. Med Chem, 4:611-616.
35. Cardoso WV, Williams MC, Mitsialis SA, Joycebrady M, Rishi AK, Brody JS (1995). Retinoic acid induces changes in the pattern of airway branching and alters epithelial cell differentiation in the developing lung in vitro. Am J Respir Cell Mol Biol, 12: 464-476.
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37. Saugstad OD (2003). Bronchopulmonary dysplasia-oxidative stress and antioxidants. Semin Neonatol, 8: 39-49.
2. Barbas CS (2007). Acute lung injury and acute respiratory distress syndrome: diagnostic hurdles. J Bras Pneumol, 33: xxv-xxvi.
3. Rubenfeld GD, Caldwell E, Peabody E et al (2005). Incidence and outcomes of acute lung injury. N Engl J Med, 353: 1685-93.
4. Parekh D, Dancer RC,Thickett DR (2011). Acute lung injury. Clin Med, 11: 615-618.
5. Esteban A, Fernández-Segoviano P, Frutos-Vivar F et al (2004). Comparison of clinical criteria for the acute respiratory distress syndrome with autopsy findings. Ann Intern Med, 141: 440-5.
6. Howrylak JA, Dolinay T, Lucht L et al (2009). Discovery of the gene signature for acute lung injury in patients with sepsis. Physiol Genomics, 37: 133-139.
7. Chen Y, Shi JX, Pan XF, Feng J, Zhao H(2013). DNA microarray-based screening of differentially expressed genes related to acute lung injury and functional analysis. Eur Rev Med Pharmacol Sci, 17: 1044-1050.
8. Guo Z, Zhao C,Zheng W(2015). RETRACTED ARTICLE: Gene expression profiles analysis identifies key genes for acute lung injury in patients with sepsis. Diagn Pathol, 9: 176.
9. Nicholson JK, Lindon JC (2008). Systems biology: Metabonomics. Nature, 455: 1054-6.
10. Holmes E, Wilson ID, Nicholson JK (2008). Metabolic phenotyping in health and disease. Cell, 134: 714-7.
11. Irizarry RA, Gautier L, Cope LM. An R Package for Analyses of Affymetrix Oligonucleotide Arrays. Springer New York, 2003.
12. Xia J,Wishart DS (2010). MSEA: a web-based tool to identify biologically meaningful patterns in quantitative metabolomic data. Nucleic Acids Res, 38: W71-7.
13. Jewison T, Su Y, Disfany FM et al (2014). SMPDB 2.0: big improvements to the Small Molecule Pathway Database. Nucleic Acids Res, 42: D478-84.
14. Kuhn M, Szklarczyk D, Franceschini A, Campillos M, Von MC, Jensen LJ, Beyer A, Bork P (2010). STITCH 2: an interaction network database for small molecules and proteins. Nucleic Acids Res, 38: 552-556.
15. Van Driel MA, Bruggeman J, Vriend G, Brunner HG, Leunissen JA (2006). A text-mining analysis of the human phenome. Eur J Hum Genet, 14: 535-542.
16. Yao Q, Xu Y, Yang H, Shang D, Zhang C, Zhang Y, Sun Z, Shi X, Li F, Han J (2015). Global Prioritization of Disease Candidate Metabolites Based on a Multi-omics Composite Network. Sci Rep, 5: 17201.
17. Wishart DS, Knox C, An CG et al (2009). HMDB: a knowledgebase for the human metabolome. Nucleic Acids Res, 37: D603-10.
18. Amberger JS, Bocchini CA, Schiettecatte F, Scott AF, Hamosh A (2015). OMIM.org: Online Mendelian Inheritance in Man (OMIM), an online catalog of human genes and genetic disorders. Nucleic Acids Res, 43: 789-798.
19. Wu X, Jiang R, Zhang MQ, Li S (2008). Network-based global inference of human disease genes. Mol Syst Biol, 4: 189.
20. Nicholson JK,Wilson ID (2003). Opinion: understanding 'global' systems biology: metabonomics and the continuum of metabolism. Nat Rev Drug Discov, 2: 668-676.
21. Ritchie MD, Holzinger ER, Li R, Pendergrass SA, Kim D (2015). Methods of integrating data to uncover genotype-phenotype interactions. Nat Rev Genet, 16: 85-97.
22. Blekherman G, Laubenbacher R, Cortes DF et al (2011). Bioinformatics tools for cancer metabolomics. Metabolomics, 7: 329-343.
23. Herceg H, Wang ZQ (2001). Functions of poly(ADP-ribose) polymerase (PARP) in DNA repair, genomic integrity and cell death. Mutat Res, 477(1-2):97-110.
24. Soldani C, Scovassi AI (2002). Poly(ADP-ribose) polymerase-1 cleavage during apoptosis: An update. Apoptosis, 7: 321-8.
25. Albertini M, Clement MG, Lafortuna CL, Caniatti M, Magder S, Abdulmalek K, Hussain SN (2000). Role of poly-(ADP-ribose) synthetase in lipopolysaccharide-induced vascular failure and acute lung injury in pigs. J Crit Care, 15: 73-83.
26. Vaschetto R, Kuiper JW, Chiang SR et al (2008). Inhibition of poly(adenosine diphosphate-ribose) polymerase attenuates ventilator-induced lung injury. Anesthesiology, 108: 261-8.
27. Kiefmann R, Heckel K, Doerger M et al (2004). Role of PARP on iNOS pathway during endotoxin-induced acute lung injury. Intensive Care Med, 30: 1421-1431.
28. Cruz CM, Rinna A, HJ, Ventura AL, Persechini PM, Ojcius DM (2007). ATP activates a reactive oxygen species-dependent oxidative stress response and secretion of proinflammatory cytokines in macrophages. J Biol Chem, 282: 2871-2879.
29. Toyokuni S, Okamoto K, Yodoi J, Hiai H (1995). Persistent oxidative stress in cancer. FEBS Lett, 358: 1-3.
30. Imai Y, Kuba K, Neely GG et al (2008). Identification of Oxidative Stress and Toll-like Receptor 4 Signaling as a Key Pathway of Acute Lung Injury. Cell, 133: 235-49.
31. Yeh CH, Yang JJ, Yang ML, Li YC, Kuan YH (2014). Rutin decreases lipopolysaccharide-induced acute lung injury via inhibition of oxidative stress and the MAPK-NF-κB pathway. Free Radic Biol Med, 69: 249-257.
32. Jiang W, Luo F, Lu Q, Liu J, Li P, Wang X, Fu Y, Hao K, Yan T, Ding X (2016). The protective effect of Trillin LPS-induced acute lung injury by the regulations of inflammation and oxidative state. Chem Biol Interact, 243: 127-134.
33. Huang R, Tian Z, Wu H (2015). Quercetin protects against lipopolysaccharide-induced acute lung injury in rats through suppression of inflammation and oxidative stress. Arch Med Sci, 11: 427-432.
34. Raja SB, Najoua M, Anouar A et al (2014). Protective Effect of ATRA on Bleomycin Induced Lung Fibrosis in Rat. Med Chem, 4:611-616.
35. Cardoso WV, Williams MC, Mitsialis SA, Joycebrady M, Rishi AK, Brody JS (1995). Retinoic acid induces changes in the pattern of airway branching and alters epithelial cell differentiation in the developing lung in vitro. Am J Respir Cell Mol Biol, 12: 464-476.
36. Ozer EA, Kumral A, Ozer E, Duman N, Yilmaz O, Ozkal S, Ozkan H (2005). Effect of retinoic acid on oxygen-induced lung injury in the newborn rat. Pediatr Pulmonol, 39: 35-40.
37. Saugstad OD (2003). Bronchopulmonary dysplasia-oxidative stress and antioxidants. Semin Neonatol, 8: 39-49.
| Files | ||
| Issue | Vol 48 No 1 (2019) | |
| Section | Original Article(s) | |
| DOI | https://doi.org/10.18502/ijph.v48i1.785 | |
| Keywords | ||
| Acute lung injury Metabolites Multi-omics network Differentially expressed genes | ||
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How to Cite
1.
WANG P-Q, LI J, ZHANG L-L, LV H-C, ZHANG S-H. Identification of Key Metabolites for Acute Lung Injury in Patients with Sepsis. Iran J Public Health. 2019;48(1):77-84.
