S1531 Shared Genetic Risk and Disease Overlap in the Gut-Lung Axis: A Systematic Review and Meta-Analysis of Inflammatory Bowel Disease and Pulmonary Comorbidity

Introduction: The gut–lung axis represents a key interface in immune-mediated disease, with inflammatory bowel disease (IBD), which encompasses Crohn's disease (CD) and ulcerative colitis (UC), being frequently comorbid with asthma and chronic obstructive pulmonary disease (COPD). While observational data suggest increased comorbidity, it remains unclear whether shared genetic susceptibility explains this overlap. We performed a systematic review and quantitative synthesis to determine the contribution of overlapping genetic loci to disease overlap between gastrointestinal and pulmonary inflammatory conditions. Methods: We performed a systematic review of GWAS and clinical cohort studies to identify genes associated with both IBD and pulmonary disease. Using publicly available odds ratios (ORs) and allele frequencies, we estimated gene-specific adjusted disease prevalence for asthma, UC, and CD. Expected overlap prevalence due to shared genetic risk was calculated using a probabilistic model. These were contrasted with observed comorbidity rates derived from U.S. Nationwide Inpatient Sample (NIS) datasets. Meta-analyses were conducted where there were multiple studies available per gene, and forest plots were generated to display effect sizes and heterogeneity. Results: Five major genes (ORMDL3, IL23R, NOD2, DENND1B, and SMAD3) had dual associations. ORMDL3 was highly associated with asthma (OR 1.44, 95% CI: 1.35–1.54) and more weakly with UC (OR 1.12, 95% CI: 0.98–1.27). NOD2 was strongly associated with CD (OR 2.20, 95% CI: 1.84–2.62) and modestly with asthma (OR 1.10, 95% CI: 1.00–1.22). Despite these, the genetically expected disease overlap (e.g., ORMDL3-mediated asthma–UC overlap: 0.0018%) was much lower than the observed overlap (∼8%) in hospitalized patients. Forest plots demonstrated wide heterogeneity, with I² ranging from 35% to 70% for various genes. Conclusion: While several genetic loci are associated with both pulmonary and gastrointestinal inflammatory diseases, the anticipated overlap via genetic risk alone is lower than the observed real-world comorbidity burden. This implicates additional factors—among them shared environmental stimuli, loss of epithelial barrier function, mucosal immunity, and microbiome disruption—in potentially propagating the gut–lung axis. These findings underscore the need for exploration of gene–environment interaction and for controlling for comorbidity in clinical risk prediction and therapeutic targeting.

Authors

Publication Details

Journal
The American Journal of Gastroenterology
Published
2025-10-01
DOI
https://doi.org/10.14309/01.ajg.0001133584.60169.82
Primary Topic
Inflammatory Bowel Disease
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

S1531 Shared Genetic Risk and Disease Overlap in the Gut-Lung Axis: A Systematic Review and Meta-Analysis of Inflammatory Bowel Disease and Pulmonary Comorbidity

Jessica Ann Lasky-Su, Samuel Y. Huang, Alexander C. Huang
The American Journal of Gastroenterology
Inflammatory Bowel Disease
article

S1531 Shared Genetic Risk and Disease Overlap in the Gut-Lung Axis: A Systematic Review and Meta-Analysis of Inflammatory Bowel Disease and Pulmonary Comorbidity

Jessica Ann Lasky-Su, Samuel Y. Huang, Alexander C. Huang
article en

Abstract

Introduction: The gut–lung axis represents a key interface in immune-mediated disease, with inflammatory bowel disease (IBD), which encompasses Crohn's disease (CD) and ulcerative colitis (UC), being frequently comorbid with asthma and chronic obstructive pulmonary disease (COPD). While observational data suggest increased comorbidity, it remains unclear whether shared genetic susceptibility explains this overlap. We performed a systematic review and quantitative synthesis to determine the contribution of overlapping genetic loci to disease overlap between gastrointestinal and pulmonary inflammatory conditions. Methods: We performed a systematic review of GWAS and clinical cohort studies to identify genes associated with both IBD and pulmonary disease. Using publicly available odds ratios (ORs) and allele frequencies, we estimated gene-specific adjusted disease prevalence for asthma, UC, and CD. Expected overlap prevalence due to shared genetic risk was calculated using a probabilistic model. These were contrasted with observed comorbidity rates derived from U.S. Nationwide Inpatient Sample (NIS) datasets. Meta-analyses were conducted where there were multiple studies available per gene, and forest plots were generated to display effect sizes and heterogeneity. Results: Five major genes (ORMDL3, IL23R, NOD2, DENND1B, and SMAD3) had dual associations. ORMDL3 was highly associated with asthma (OR 1.44, 95% CI: 1.35–1.54) and more weakly with UC (OR 1.12, 95% CI: 0.98–1.27). NOD2 was strongly associated with CD (OR 2.20, 95% CI: 1.84–2.62) and modestly with asthma (OR 1.10, 95% CI: 1.00–1.22). Despite these, the genetically expected disease overlap (e.g., ORMDL3-mediated asthma–UC overlap: 0.0018%) was much lower than the observed overlap (∼8%) in hospitalized patients. Forest plots demonstrated wide heterogeneity, with I² ranging from 35% to 70% for various genes. Conclusion: While several genetic loci are associated with both pulmonary and gastrointestinal inflammatory diseases, the anticipated overlap via genetic risk alone is lower than the observed real-world comorbidity burden. This implicates additional factors—among them shared environmental stimuli, loss of epithelial barrier function, mucosal immunity, and microbiome disruption—in potentially propagating the gut–lung axis. These findings underscore the need for exploration of gene–environment interaction and for controlling for comorbidity in clinical risk prediction and therapeutic targeting.

The American Journal of GastroenterologyVol. 120(10S2)
Openalex Percentile: Top 59%
Inflammatory Bowel Disease
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.