Gut Microbiota and Primary Liver Cancer: Mendelian Randomization and Network Pharmacology Used to Predict Potential
Qingliang Chen1, Lin Jin2, Suping Ding3
1Department of Radioactive Intervention Department, Henan No.3 Provincial People's Hospital, Zhengzhou, Henan, China.
Objective:
The objective of this study is to employ Mendelian randomization (MR) to screen for gut microbiota (GM) exhibiting causal genetic effects on primary liver cancer (PLC) development and to predict promising traditional Chinese medicine (TCM) candidates capable of intervening in PLC by modulating the GM.
Methods:
Summary statistics from genome-wide association studies (GWASs) examining the relationship between GM and PLC were retrieved from the IEU OpenGWAS database. MR analysis was conducted using the two-sample MR package in R, employing the inverse variance weighted (IVW) method as the primary approach for assessing genetic causal effects. Functional enrichment analysis was performed on genes proximal to the instrumental variables (IVs) to investigate the signaling pathways through which the implicated microbiota may contribute to PLC pathogenesis. The CTD and Coremine Medical databases were combined to predict TCM compounds potentially regulating the genes proximal to the IVs.
Result:
The MR analysis identified nine taxonomic groups of GM exhibiting genetically predicted causal effects on PLC development. Among these, the Family XI (OR = 0.680, 95% CI: 0.469-0.985, p = 0.041), the genus Anaerotruncus (OR = 0.446, 95% CI: 0.228-0.873, p = 0.018), the genus Coprococcus 2 (OR = 0.440, 95% CI: 0.208-0.929, p = 0.031), the genus Escherichia Shigella (OR = 0.430, 95% CI: 0.216-0.857, p = 0.016), and the order Lactobacillales (OR = 0.517, 95% CI: 0.280-0.955, p = 0.035) were associated with a reduced risk of PLC. Conversely, the genus Barnesiella (OR = 2.594, 95% CI: 1.388-4.849, p = 0.003), the genus Catenibacterium (OR = 1.749, 95% CI: 1.003-3.048, p = 0.049), the genus Ruminococcus 2 (OR = 1.808, 95% CI: 1.066-3.068, p = 0.028), and Mollicutes RF9 (OR = 1.707, 95% CI: 1.010-2.884, p = 0.046) were associated with an elevated risk of PLC. The most frequently represented Chinese medicinal herbs predominantly include Camellia sinensis root, Curcuma longa L., Salvia miltiorrhiza, Triticum aestivum L., Panax ginseng C. A. Meyer, Panax notoginseng F.H. Chen, Radix Curcumae, Aucklandia lappa, Scutellaria baicalensis, and Zingiber officinale Rose., among others. GO enrichment analysis revealed that these genes were significantly enriched in biological processes including positive regulation of the ERK1/ERK2 signaling pathway, posttranslational protein modification (such as deglutamylation), synaptic vesicle exocytosis, and urea transport. KEGG pathway enrichment analysis demonstrated predominant enrichment of these genes in the neurotrophin signaling pathway and the cAMP signaling pathway.
Conclusion:
This study provides novel insights for developing GM-based TCM strategies for PLC prevention and treatment.
Insights
This study used Mendelian randomization to identify gut microbiota (GM) causally linked to primary liver cancer (PLC). Certain GM reduced PLC risk, while others increased it, suggesting potential TCM interventions.
Area of Science:
- Genetics and Genomics
- Microbiology
- Oncology
Background:
- Primary liver cancer (PLC) pathogenesis is complex and influenced by various factors.
- The gut microbiota (GM) plays a significant role in host health and disease, including cancer development.
- Understanding the causal relationship between GM and PLC is crucial for developing effective prevention and treatment strategies.
Purpose of the Study:
- To identify specific gut microbiota (GM) taxa with genetically predicted causal effects on primary liver cancer (PLC) development using Mendelian randomization (MR).
- To predict potential traditional Chinese medicine (TCM) candidates that can modulate the identified GM for PLC intervention.
Main Methods:
- Genome-wide association study (GWAS) summary statistics for GM and PLC were analyzed using a two-sample Mendelian randomization (MR) approach.
- Inverse variance weighted (IVW) method was the primary analysis technique to assess genetic causal effects.
- Functional enrichment analysis (GO and KEGG) and database mining (CTD and Coremine Medical) were employed to identify pathways and predict TCM candidates.
Main Results:
- Nine GM taxonomic groups showed genetically predicted causal effects on PLC.
- Reduced PLC risk was associated with Family XI, *Anaerotruncus*, *Coprococcus* 2, *Escherichia Shigella*, and Lactobacillales.
- Elevated PLC risk was linked to *Barnesiella*, *Catenibacterium*, *Ruminococcus* 2, and Mollicutes RF9.
- Enrichment analysis implicated pathways like ERK1/ERK2 signaling, protein modification, and neurotrophin signaling.
- Potential TCM interventions include *Camellia sinensis* root, *Curcuma longa*, and *Salvia miltiorrhiza*.
Conclusions:
- This study identified specific gut microbiota with causal links to primary liver cancer risk.
- The findings suggest that modulating gut microbiota through traditional Chinese medicine could be a viable strategy for PLC prevention and treatment.
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