asthma
Definition
Asthma is a chronic inflammatory disease of the airways characterized by reversible airflow obstruction, bronchial hyperresponsiveness, and recurrent episodes of wheezing, breathlessness, and coughing. The pathophysiology involves complex interactions between genetic susceptibility and environmental triggers, leading to immune dysregulation with predominant Th2-mediated inflammation, eosinophil infiltration, mucus hypersecretion, and airway remodeling. Key molecular players include cytokines (IL-4, IL-5, IL-13), IgE antibodies, mast cells, and smooth muscle contraction pathways. Asthma affects over 300 million people worldwide and represents a significant research focus for understanding inflammatory disease mechanisms, identifying biomarkers for disease endotypes, and developing targeted therapeutics including biologics against specific immune pathways.
Visualize asthma in Nodes Bio
Researchers can map asthma's multi-scale disease networks in Nodes Bio, connecting genetic variants, inflammatory mediators, immune cell populations, and clinical phenotypes. Visualize cytokine signaling cascades, gene-environment interactions, and drug-target relationships to identify novel therapeutic intervention points. Network analysis reveals disease endotype clusters and helps stratify patient populations based on molecular signatures for precision medicine approaches.
Visualization Ideas:
- Cytokine signaling networks showing Th2 inflammatory cascade with IL-4, IL-5, and IL-13 pathways
- Gene-environment interaction networks linking genetic variants to allergen exposures and disease outcomes
- Drug-target networks mapping biologic therapies to their molecular targets and downstream pathway effects
Example Use Case
A pharmaceutical team investigating severe eosinophilic asthma uses network visualization to map the IL-5 signaling pathway and its downstream effects. They integrate transcriptomic data from bronchial biopsies with known protein-protein interactions, revealing that blocking IL-5 receptor alpha affects 47 connected genes. The network analysis identifies three previously unrecognized feedback loops involving CCR3 and eotaxins, suggesting combination therapy targets. This systems-level view helps explain why some patients respond poorly to anti-IL-5 monotherapy.