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An inflammatory response is a localized, nonspecific immune reaction that occurs when a tissue is injured. It is characterized by redness, swelling, heat, and pain, which are commonly called the cardinal signs and symptoms of inflammation. Inflammation can sometimes result in a loss of function.
Inflammation can be triggered by various stimuli, such as impact, abrasion, chemical irritation, infections, and extreme hot or cold temperatures. These can damage cells and connective tissue fibers,...
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Immune and inflammatory resolution pathways through multi-omics using the AI-based Network Integration.

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This study introduces an AI-based Network Integration approach to untangle complex multi-omics data, revealing a biological link between lipid mediators and glycosylation in immune regulation and inflammation resolution.

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Area of Science:

  • Immunology
  • Systems Biology
  • Genomics
  • Metabolomics
  • Glycomics

Background:

  • Multi-omics data integration is challenging due to data heterogeneity, high dimensionality, and missing values.
  • Understanding immune regulation and inflammation resolution requires integrating diverse molecular profiles.
  • Existing methods struggle to model complex inter-omics relationships effectively.

Purpose of the Study:

  • To propose and validate an AI-based Network Integration approach for multi-omics data.
  • To investigate the relationship between immunoglobulin G N-glycans (glycans) and specialized pro-resolving lipid mediators (SPMs) in immune and inflammatory pathways.
  • To identify molecular causal networks and bridging molecules influencing immune regulation.

Main Methods:

  • Cross-sectional multi-omics study (genetic, glycomic, lipidomic data).
  • AI-based Network Integration for modeling inter-omics connectivity.
  • Pairwise association analysis and conditional analysis.
  • Principal Component Analysis (PCA) for polygenic factor derivation.
  • Granularity Directed Acyclic Graph (G-DAG) algorithm for Mendelian randomization.

Main Results:

  • AI-based Network Integration successfully modeled complex biological system influences across omics layers.
  • Identified 10 significant glycan-SPM associations, with two bridging molecules (5-HEPE SPM and GP21 glycan) mediating these links.
  • Discovered that both 5-HEPE and GP21 are under polygenic control, with distinct roles as receivers and broadcasters, respectively.
  • Revealed a biological link between SPM lipidomics variations and glycosylation changes.

Conclusions:

  • The AI-based Network Integration approach provides interpretable and biologically meaningful insights from noisy multi-omics data.
  • Findings suggest a novel connection between lipid mediators and glycan-mediated immune regulation and inflammation resolution.
  • The study highlights the utility of integrating genetic, glycomic, and lipidomic data for uncovering complex biological pathways.