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Meta-Analysis
. 2023 Sep 1;21(1):587.
doi: 10.1186/s12967-023-04278-1.

Interplay of chronic obstructive pulmonary disease and colorectal cancer development: unravelling the mediating role of fatty acids through a comprehensive multi-omics analysis

Affiliations
Meta-Analysis

Interplay of chronic obstructive pulmonary disease and colorectal cancer development: unravelling the mediating role of fatty acids through a comprehensive multi-omics analysis

Youtao Zhou et al. J Transl Med. .

Abstract

Background: Chronic obstructive pulmonary disease (COPD) patients often exhibit gastrointestinal symptoms, A potential association between COPD and Colorectal Cancer (CRC) has been indicated, warranting further examination.

Methods: In this study, we collected COPD and CRC data from the National Health and Nutrition Examination Survey, genome-wide association studies, and RNA sequence for a comprehensive analysis. We used weighted logistic regression to explore the association between COPD and CRC incidence risk. Mendelian randomization analysis was performed to assess the causal relationship between COPD and CRC, and cross-phenotype meta-analysis was conducted to pinpoint crucial loci. Multivariable mendelian randomization was used to uncover mediating factors connecting the two diseases. Our results were validated using both NHANES and GEO databases.

Results: In our analysis of the NHANES dataset, we identified COPD as a significant contributing factor to CRC development. MR analysis revealed that COPD increased the risk of CRC onset and progression (OR: 1.16, 95% CI 1.01-1.36). Cross-phenotype meta-analysis identified four critical genes associated with both CRC and COPD. Multivariable Mendelian randomization suggested body fat percentage, omega-3, omega-6, and the omega-3 to omega-6 ratio as potential mediating factors for both diseases, a finding consistent with the NHANES dataset. Further, the interrelation between fatty acid-related modules in COPD and CRC was demonstrated via weighted gene co-expression network analysis and Kyoto Encyclopedia of Genes and Genomes enrichment results using RNA expression data.

Conclusions: This study provides novel insights into the interplay between COPD and CRC, highlighting the potential impact of COPD on the development of CRC. The identification of shared genes and mediating factors related to fatty acid metabolism deepens our understanding of the underlying mechanisms connecting these two diseases.

Keywords: Chronic obstructive pulmonary disease; Colorectal cancer; Fatty acid; Mediating factor; Multi-omics.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Fig. 1
Fig. 1
Exploring multi-level investigation using NHANES, GWAS, and GEO databases
Fig. 2
Fig. 2
Effects of characteristics on risk of colon cancer in NHANES. P value < 0.05 was considered statistically significant. OR odds ratio, CI confidence intervals, COPD chronic obstructive pulmonary disease
Fig. 3
Fig. 3
Manhattan plot of GWAS results of the COPD outcomes and Colorectal Cancer. The x-axis represents the SNPs locus on the chromosome, and the y-axis represents the p-value of the SNPs locus. The red and blue reference lines represent −log10 logarithm of p-values of 5e−08 and 1e−05, respectively. COPD chronic obstructive pulmonary disease
Fig. 4
Fig. 4
This forest plot represents the 9 lipid-related mediators identified by MVMR analysis with COPD as exposure and colorectal cancer as outcome. An odds ratio (OR) greater than 1 indicates that the corresponding mediator increases the risk of colorectal cancer, while an OR less than 1 indicates a protective effect. MVMR Multivariable Mendelian Randomization analysis
Fig. 5
Fig. 5
Protein–protein interaction network diagram annotated from genes obtained after performing cross-trait meta-analysis between COPD and CRC. The yellow nodes represent four genes (GNAS, RHPN2, FAM163B, STARD3), which were annotated with SNPs that have p-values smaller than 5e−08
Fig. 6
Fig. 6
A Visualization of lipid-related modules enriched through WGCNA analysis across GSE29621, GSE17536, GSE15781, and GSE57148 datasets. The size of each dot represents the number of genes enriched in the corresponding pathway, while the color represents the respective module. B Extracting fatty-acid-related modules and conducting correlation analysis using module eigengenes in COPD and CRC

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