Targeting IL-13 and IL-4 in Asthma: Therapeutic Implications on Airway Remodeling in Severe Asthma
Bibliographic record
Abstract
Asthma is a chronic respiratory disorder affecting individuals across all age groups. It is characterized by airway inflammation and remodeling and leads to progressive airflow restriction. While corticosteroids remain a mainstay therapy, their efficacy is limited in severe asthma due to genetic and epigenetic alterations, as well as elevated pro-inflammatory cytokines interleukin-4 (IL-4), interleukin-13 (IL-13), and interleukin-5 (IL-5), which drive structural airway changes including subepithelial fibrosis, smooth muscle hypertrophy, and goblet cell hyperplasia. This underscores the critical need for biologically targeted therapies. This review systematically examines the roles of IL-4 and IL-13, key drivers of type-2 inflammation, in airway remodeling and their potential as therapeutic targets. IL-4 orchestrates eosinophil recruitment, immunoglobulin class switching, and Th2 differentiation, whereas IL-13 directly modulates structural cells, including fibroblasts and epithelial cells, to promote mucus hypersecretion and extracellular matrix (ECM) deposition. Despite shared signaling pathways, IL-13 emerges as the dominant cytokine in remodeling processes including mucus hypersecretion, fibrosis and smooth muscle hypertrophy. While IL-4 primarily amplifies inflammatory cascades by driving IgE switching, promoting Th2 cell polarization that sustain cytokine release, and inducing chemokines to recruit eosinophils. In steroid-resistant severe asthma, biologics targeting IL-4/IL-13 show promise in reducing exacerbations and eosinophilic inflammation. However, their capacity to reverse established remodeling remains inconsistent, as clinical trials prioritize inflammatory biomarkers over long-term structural outcomes. This synthesis highlights critical gaps in understanding the durability of IL-4/IL-13 inhibition on airway structure and advocates for therapies combining biologics with remodeling-specific strategies. Through the integration of mechanistic insights and clinical evidence, this review emphasizes the need for long-term studies utilizing advanced imaging, histopathological techniques, and patient-reported outcomes to evaluate how IL-4/IL-13-targeted therapies alter airway remodeling and symptom burden, thereby informing more effective treatment approaches for severe, steroid-resistant asthma. Schematic representation of the roles of IL-4 and IL-13 in driving inflammation and airway remodeling in asthma. IL-4 primarily contributes to inflammation by (1) promoting Type 2 helper T (Th2) cell differentiation from naïve T cells, (2) stimulating IgE production by B cells, and (3) enhancing eosinophil recruitment. Conversely, IL-13 is predominantly involved in airway remodeling through (1) inducing goblet cell hyperplasia and excessive mucus production, (2) promoting fibrosis, (3) driving smooth muscle hypertrophy and hyperresponsiveness, and (4) activating or damaging airway epithelial cells (AEC).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".