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

 bidirectional relationship btwn GI / Pulmonary diseases

- Genetic dispositions

- Shared immunological pathways

- biologic therapies

Genetic Associations 

DENND1B T cell receptor signaling / endocytic trafficking, SMAD3 TGF-beta receptors to nucleus influencing gene expression

STAT4 IL-12 in lymphocytes promoting TH1 differentiation

SLC22A4/5 moudling responses in asthma

NOD2 (CARD15)

IL23R Interleukin 23 Receptor

ORMDL3 Sphingolipid biosynthesis regulator 3

PGLYRP1 peptidoglycan recognition protein 1 - contributing to innate immune responses

Project Overview: Investigating the Gut-Lung Axis in IBD and Pulmonary Diseases

Objective

To elucidate the bidirectional relationship between gastrointestinal and pulmonary diseases, focusing on shared immunological pathways, genetic predispositions, and the role of biologic therapies.

Background

• Immunological Crosstalk: Emerging evidence suggests that gut-derived immune responses can influence pulmonary health, and vice versa.

• Genetic Associations: Certain genetic loci, such as NOD2, have been implicated in both Crohn's disease and pulmonary conditions like COPD.

• Therapeutic Implications: Biologic agents (e.g., anti-TNF therapies) used in IBD management have been associated with pulmonary side effects, including interstitial pneumonitis.

 

Methodology

1. Systematic Literature Review

• Databases: PubMed, Embase, Cochrane Library

• Search Terms: "gut-lung axis," "inflammatory bowel disease," "interstitial lung disease," "biologic therapy," "genetic polymorphisms"

• Inclusion Criteria:

o Studies involving human subjects

o Randomized controlled trials (RCTs), cohort studies, and case-control studies

o Publications within the last 10 years

o Lippincott Journals+5Wikipedia+5Time+5Nature

2. Data Extraction and Analysis

• Parameters:

o Patient demographics

o Type and duration of IBD

o Pulmonary manifestations

o Genetic markers identified

o Type of biologic therapy used

o Outcomes measured

• Analysis Tools:

o Use of statistical software (e.g., RevMan) for meta-analysis

o Assessment of heterogeneity and publication bias

Key Areas of Focus

1. Genetic Intersections

• Shared Loci: Investigate loci such as DENND1B, SMAD3, and SLC22A4/5 for their roles in both IBD and pulmonary diseases.

• Mendelian Randomization Studies: Utilize these to assess causal relationships between genetic variants and disease manifestations.

2. Biologic Therapies and Pulmonary Outcomes

• Anti-TNF Agents: Evaluate the incidence of pulmonary side effects in patients treated with infliximab, adalimumab, and certolizumab.

• Other Biologics: Assess the safety profiles of ustekinumab and vedolizumab concerning lung health.

3. Microbiota and Immune Modulation

• Gut Microbiome: Explore how alterations in gut flora may influence pulmonary immune responses.

• Therapeutic Interventions: Consider the impact of probiotics and fecal microbiota transplantation (FMT) on both gut and lung health.

Abstract Structure

1. Title: "Exploring the Gut-Lung Axis: Implications for Inflammatory Bowel Disease and Pulmonary Health"

2. Background: Brief overview of the gut-lung connection and its clinical significance.

3. Methods: Summary of the systematic review and meta-analysis approach.

4. Results: Key findings highlighting genetic links and therapy-related pulmonary outcomes.

5. Conclusion: Implications for clinical practice and future research directions.Wikipedia+5MDPI+5chestpulmonary.org+5

Submission Guidelines

• Format: Follow ACG's abstract submission requirements, typically including word limits and structured headings.

• Deadline: Ensure submission before the specified deadline for the upcoming ACG conference.

• Supplementary Materials: Include tables, figures, and references as per guidelines.Lippincott Journals+5Nature+5PubMed+5

 

📚 Suggested Reading

• The Gut-Lung Axis: Mendelian Randomization Identifies a Causal Association Between Inflammatory Bowel Disease and Interstitial Lung Disease

Heart Lung. 2023 Sep-Oct;61:120-126.

Link

• Genetic Evidence of Bidirectional Mendelian Randomization Study on the Causality Between Gut Microbiome and Respiratory Diseases

Scientific Reports. 2024;14:25550.

Link

• Advances in Gut-Lung Axis Research: Clinical Perspectives

Frontiers in Immunology. 2025.

Link

 

By conducting this comprehensive analysis, the project aims to bridge the knowledge gap between gastrointestinal and pulmonary health, offering insights that could inform clinical practices and therapeutic strategies.

Key Genetic Loci in IBD and Associated Pulmonary Conditions

1. NOD2 (CARD15)

• Function: Encodes an intracellular pattern recognition receptor involved in bacterial peptidoglycan sensing.

• Association: Strongly linked to Crohn's disease susceptibility, particularly with ileal involvement.

• Pulmonary Connection: Polymorphisms may contribute to impaired mucosal immunity, potentially influencing chronic obstructive pulmonary disease (COPD) pathogenesis.

2. IL23R (Interleukin-23 Receptor)

• Function: Plays a pivotal role in the differentiation and maintenance of Th17 cells, crucial for mucosal immunity.

• Association: Variants confer protection against both Crohn's disease and ulcerative colitis.

• Pulmonary Connection: Th17-mediated responses are implicated in asthma and other inflammatory airway diseases.Wikipedia

3. ORMDL3 (ORMDL Sphingolipid Biosynthesis Regulator 3)

• Function: Regulates sphingolipid synthesis and endoplasmic reticulum-mediated calcium signaling.

• Association: Variants associated with childhood asthma and, to a lesser extent, ulcerative colitis.

• Pulmonary Connection: Overexpression linked to airway hyperresponsiveness and remodeling in asthma models.Wikipedia

4. DENND1B (DENN Domain Containing 1B)

• Function: Involved in T-cell receptor signaling and endocytic trafficking.

• Association: Identified as a susceptibility locus for both asthma and Crohn's disease.

• Pulmonary Connection: Variants may influence T-cell mediated inflammation in asthma.

5. SLC22A4/5 (Solute Carrier Family 22 Members 4 and 5)

• Function: Organic cation transporters involved in the uptake of various molecules, including drugs and endogenous compounds.

• Association: Polymorphisms linked to Crohn's disease susceptibility.

• Pulmonary Connection: Potential role in modulating responses to inhaled medications in asthma.

6. SMAD3 (SMAD Family Member 3)

• Function: Transduces signals from TGF-β receptors to the nucleus, influencing gene expression.

• Association: Variants associated with increased risk for Crohn's disease and asthma.

• Pulmonary Connection: Involved in airway remodeling and fibrosis in chronic lung diseases.

7. STAT4 (Signal Transducer and Activator of Transcription 4)

• Function: Mediates responses to IL-12 in lymphocytes, promoting Th1 differentiation.

• Association: Polymorphisms linked to ulcerative colitis and other autoimmune diseases.

• Pulmonary Connection: May influence susceptibility to asthma through modulation of immune responses.

8. PGLYRP1 (Peptidoglycan Recognition Protein 1)

• Function: Recognizes bacterial peptidoglycan, contributing to innate immune responses.

• Association: Variants associated with IBD and asthma, suggesting a role in mucosal immunity.

• Pulmonary Connection: Deficiency in murine models leads to altered asthma phenotypes, indicating a role in airway inflammation.

Key Genetic Loci in IBD and Associated Pulmonary Conditions

NOD2 (CARD15) Intracellular pattern recognition receptor in peptidoglycan sensing, Mucosal immunity, Crohn’s disease + COPD

IL23R (Interleukin-23 Receptor) Th17 cells, crucial for mucosal immunity, Variants confer protection against both Crohn's disease and ulcerative colitis

ORMDL3 (ORMDL Sphingolipid Biosynthesis Regulator 3) Regulates sphingolipid synthesis and endoplasmic reticulum-mediated calcium signaling, childhood asthma + UC

DENND1B (DENN Domain Containing 1B) Involved in T-cell receptor signaling and endocytic trafficking asthma and crohn’s

SLC22A4/5 (Solute Carrier Family 22 Members 4 and 5) Organic cation transporters involved in the uptake of various molecules, including drugs and endogenous compounds, Polymorphisms linked to Crohn's disease susceptibility, Potential role in modulating responses to inhaled medications in asthma.

SMAD3 (SMAD Family Member 3) Function: Transduces signals from TGF-β receptors to the nucleus, influencing gene expression. increased risk for Crohn's disease and asthma. Pulmonary Connection: Involved in airway remodeling and fibrosis in chronic lung diseases.

STAT4 (Signal Transducer and Activator of Transcription 4) Mediates responses to IL-12 in lymphocytes, promoting Th1 differentiation, Polymorphisms linked to UC and other AI diseases.

PGLYRP1 (Peptidoglycan Recognition Protein 1) Recognizes bacterial peptidoglycan, contributing to innate immune responses, mucosal immunity Pulmonary Connection: Deficiency in murine models leads to altered asthma phenotypes, indicating a role in airway inflammation.

 

Summary of Meta-Analyses for Key Genetic Loci

1. NOD2 (CARD15) – Crohn’s Disease

• Variants Analyzed: R702W, G908R, 1007fs

• Findings:

o R702W: OR = 2.20 (95% CI: 1.84–2.62)

o G908R: OR = 2.99 (95% CI: 2.38–3.74)

o 1007fs: OR = 4.09 (95% CI: 3.23–5.18)

o Homozygous or compound heterozygous carriers: OR = 17.1 (95% CI: 10.7–27.2)

• Source: NatureNature+5Nature+5MDPI+5

2. IL23R – Crohn’s Disease

• Variants Analyzed: rs7517847, rs10889677, rs2201841, rs11209026

• Findings:

o rs7517847G allele: OR = 0.699 (95% CI: 0.659–0.741)

o rs10889677A allele: OR = 1.393 (95% CI: 1.328–1.461)

o rs2201841C allele: OR = 1.368 (95% CI: 1.301–1.438)

o rs11209026G allele: OR = 0.435 (95% CI: 0.376–0.503)

• Source: NaturePubMed+4Nature+4Wiley Online Library+4

3. ORMDL3 – Asthma

• Variant Analyzed: rs7216389

• Findings:

o OR = 1.44 (95% CI: 1.35–1.54)

• Source: PMCPMC+5JAC Online+5e-Century Publishing Corporation+5

4. DENND1B – Asthma

• Variant Analyzed: rs2786098

• Findings:

o OR = 2.6 (95% CI not specified)

• Source: PubMedMDPI+35QIMR Genetic Epidemiology Laboratory+35ResearchGate+35QIMR Genetic Epidemiology Laboratory+10PLOS+10ScienceDirect+10

5. SLC22A4/SLC22A5 – Crohn’s Disease

• Variants Analyzed: SLC22A4 C1672T, SLC22A5 G-207C

• Findings:

o SLC22A4 C1672T: OR = 0.90 (95% CI: 0.57–1.40)

o SLC22A5 G-207C: OR = 0.90 (95% CI: 0.65–1.23)

• Source: PubMedOAText+4Gastro Journal+4PubMed+4PubMed+1Nature+1

6. SMAD3 – Crohn’s Disease

• Findings:

o SMAD3 variants are associated with increased risk of recurrent surgery in Crohn's disease patients.

• Source: PMCPMC+1Oxford Academic+1

7. STAT4 – Ulcerative Colitis

• Variant Analyzed: rs7574865

• Findings:

o No significant association with ulcerative colitis was found in the meta-analysis.

• Source: PubMedResearchGate+19PubMed+19ProQuest+19

8. PGLYRP1 – Asthma

• Findings:

o PGLYRP1 variants are associated with increased risk of asthma, with ORs ranging from 2.34 to 3.95.

• Source: PMCNature+2PMC+2e-aair.org+2

 

•  Data Collection:

• Gather individual-level data from studies included in the meta-analyses, if available.

• Ensure data includes genotype frequencies, sample sizes, and effect estimates.

•  Statistical Analysis:

• Use meta-analysis software (e.g., RevMan, STATA, or R with the 'meta' package) to calculate pooled odds ratios.

• Assess heterogeneity using I² statistics and perform subgroup analyses if necessary.

•  Manuscript Preparation:

• Structure your manuscript according to ACG guidelines, including sections on background, methods, results, discussion, and conclusions.

• Include forest plots and funnel plots to visualize findings and assess publication bias.

•  Submission to ACG:

• Prepare an abstract summarizing your findings for submission to the ACG annual meeting.

• Follow ACG's specific submission guidelines and deadlines.

 

 

 

 

Meta-Analysis Results (Random Effects Model):

• Pooled log OR: ~1.018

• Pooled OR: ~2.77

• 95% CI (log OR): approximately (0.66, 1.37)

• Interpretation: The pooled analysis suggests that these genetic variants are significantly associated with an increased risk of disease, with an overall odds ratio of ~2.77

 

Shared Genetic Risk and Disease Overlap in the Gut–Lung Axis: A Systematic Review and Meta-Analysis

Introduction

The gut lung axis is an emerging field of research interfacing immune mediated disease such as inflammatory bowel disease including Crohn’s disease and ulcerative colitis frequently co-occuring with asthma

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

 

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.

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.

Discussion

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.