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October 2, 2025Journal of Gastroenterology and Hepatology

Decoding the Molecular Landscape of Inflammatory Bowel Disease: A Mendelian Randomization and Machine Learning Analysis

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Authors

XZXuwen ZhengCZChenran ZhangMZMuhammad Zubair

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Overview

Two-phase mendelian randomization reveals causal associations with plasma proteins in inflammatory bowel disease, indicating potential therapeutic targets.

Key Points

  • The study identifies proteins significantly associated with inflammatory bowel disease risk, validating findings across cohorts.
  • A two-phase approach utilized summary-data‐based mendelian randomization, highlighting genes associated with Crohn's disease and ulcerative colitis.
  • Machine learning models indicated potential therapeutic targets, such as glucokinase regulatory protein and hepatocyte growth factor-like protein.
  • Findings contribute to precision medicine through improved diagnosis and treatment of inflammatory bowel disease, with noted limitations in diverse population validation.

Cite This Study

Zheng et al. (2025) studied this question.

synapsesocial.com/papers/68de68ea83cbc991d0a2161dhttps://doi.org/10.1111/jgh.70085
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Also Consider

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  1. 1Evaluating the causal effect of circulating proteome on the risk of inflammatory bowel disease-related traits using Mendelian randomization2024 · 1 citations
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  3. 3Integrating plasma proteomics with genome-wide association data to identify novel drug targets for inflammatory bowel disease2024 · 4 citations
  4. 4Exploring inflammatory bowel disease therapy targets through druggability genes: a Mendelian randomization study2024 · 1 citations
  5. 5Effect of immune cells and plasma metabolites on inflammatory bowel disease: Two-sample Mendelian randomization study and mediation analysis2025