Multiple Sclerosis Drives Gastric Cancer via Shared Inflammatory Pathways: A Mendelian Randomization Study

Abstract

Background The causal relationship between Multiple Sclerosis (MS) and Gastric Cancer (GC) remains unclear despite reports suggesting that MS, an autoimmune disease, may contribute to the development of various tumors.

Methods Mendelian Randomization (MR) analysis was employed to explore the potential causal relationship between MS and GC. Subsequently, the GEO database was utilized to identify differentially expressed genes (DEGs) that are commonly associated with both MS and GC, thereby revealing the shared molecular mechanisms underlying these two diseases.

Results The MR analysis indicated that MS significantly increased the risk of GC, demonstrating a positive causal effect. However, reverse analysis from GC to MS did not reveal any significant causal relationships. The sensitivity analysis supported the evidence of a positive causal effect of MS on GC. Transcriptomic data analysis identified shared DEGs between MS and GC, particularly those involved in immune regulation, stromal formation, and cell migration, suggesting that these genes operate through similar biological pathways in both diseases.

Conclusion These findings underscore the intricate interplay between autoimmune disorders and gastrointestinal malignancies, offering potential molecular targets for the personalized management of MS and GC prevention.

Competing Interest Statement

The authors have declared no competing interest.

Clinical Trial

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Funding Statement

The author(s) received no specific funding for this work.

Author Declarations

I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.

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We employed publicly available GWAS summary statistics data obtained from the OpenGWAS database, which collects data from studies conducted with appropriate informed consent protocols approved by institutional review boards.

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Data Availability

All relevant data are within the manuscript and its Supporting Information files.

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