» Articles » PMID: 39604493

Exploring Molecular Mechanisms of Postoperative Delirium Through Multi-omics Strategies in Plasma Exosomes

Overview
Journal Sci Rep
Specialty Science
Date 2024 Nov 28
PMID 39604493
Authors
Affiliations
Soon will be listed here.
Abstract

Currently, the diagnosis of delirium is solely based on clinical observation, lacking objective diagnostic tools, and the regulatory networks and pathological mechanisms behind it are not yet fully understood. Exosomes have garnered considerable interest as potential biomarkers for a variety of illnesses. This research aimed to delineate both the proteomic and metabolomic landscapes inherent to exosomes, assessing their diagnostic utility in postoperative delirium (POD) and understanding the underlying pathophysiological frameworks. Integrated analyses of proteomics and metabolomics were conducted on exosomes derived from plasma of individuals from both the non-postoperative delirium (NPOD) control group and the POD group. Subsequently, the study utilized the Connectivity Map (CMap) methodology for the identification of promising small-molecule drugs and carried out molecular docking assessments to explore the binding affinities with the enzyme MMP9 of these identified molecules. We identified significant differences in exosomal metabolites and proteins between the POD and control groups, highlighting pathways related to neuroinflammation and blood-brain barrier (BBB) integrity. Our CMap analysis identified potential small-molecule therapeutics, and molecular docking studies revealed two compounds with high affinity to MMP9, suggesting a new therapeutic avenue for POD. This study highlights MMP9, TLR2, ICAM1, S100B, and glutamate as key biomarkers in the pathophysiology of POD, emphasizing the roles of neuroinflammation and BBB integrity. Notably, molecular docking suggests mirin and orantinib as potential inhibitors targeting MMP9, providing new therapeutic avenues. The findings broaden our understanding of POD mechanisms and suggest targeted strategies for its management, reinforcing the importance of multidimensional biomarker analysis and molecular targeting in POD intervention.

References
1.
Wang T, Shao W, Huang Z, Tang H, Zhang J, Ding Z . MOGONET integrates multi-omics data using graph convolutional networks allowing patient classification and biomarker identification. Nat Commun. 2021; 12(1):3445. PMC: 8187432. DOI: 10.1038/s41467-021-23774-w. View

2.
Romero-Perez D, Fricovsky E, Yamasaki K, Griffin M, Barraza-Hidalgo M, Dillmann W . Cardiac uptake of minocycline and mechanisms for in vivo cardioprotection. J Am Coll Cardiol. 2008; 52(13):1086-94. PMC: 2572824. DOI: 10.1016/j.jacc.2008.06.028. View

3.
Tian C, Kasavajhala K, Belfon K, Raguette L, Huang H, Migues A . ff19SB: Amino-Acid-Specific Protein Backbone Parameters Trained against Quantum Mechanics Energy Surfaces in Solution. J Chem Theory Comput. 2019; 16(1):528-552. DOI: 10.1021/acs.jctc.9b00591. View

4.
Hannocks M, Zhang X, Gerwien H, Chashchina A, Burmeister M, Korpos E . The gelatinases, MMP-2 and MMP-9, as fine tuners of neuroinflammatory processes. Matrix Biol. 2017; 75-76:102-113. DOI: 10.1016/j.matbio.2017.11.007. View

5.
Achek A, Yesudhas D, Choi S . Toll-like receptors: promising therapeutic targets for inflammatory diseases. Arch Pharm Res. 2016; 39(8):1032-49. DOI: 10.1007/s12272-016-0806-9. View