Evidence map›Paper›PMID 39964572›Full record

ArticleDiscover oncology2025

Genetic insights into the shared molecular mechanisms of Crohn's disease and breast cancer: a Mendelian randomization and deep learning approach.

Zhuang Zhuang Wang, Ju Lin Yang, Zong Yao Zhang, Pei Bin Wang

Abstract read
In one paragraph

Article in Discover oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Zhuang Zhuang Wang *Graduate School of Bengbu Medical University, No. 2600 Donghai Avenue, Bengbu, 233030, China.
Ju Lin Yang *Graduate School of Bengbu Medical University, No. 2600 Donghai Avenue, Bengbu, 233030, China.
Zong Yao ZhangDepartment of General Surgery, The First Hospital of Anhui University of Science and Technology, No.203 Huai Bin Road, Tian Jia' an District, Huainan, 232007, China. zzy17612429244@126.com.
Pei Bin WangDepartment of General Surgery, The First Hospital of Anhui University of Science and Technology, No.203 Huai Bin Road, Tian Jia' an District, Huainan, 232007, China. zhouboweike@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The objective of this study was to explore the potential genetic link between Crohn's disease and breast cancer, with a focus on identifying druggable genes that may have therapeutic relevance. We assessed the causal relationship between these diseases through Mendelian randomization and investigated gene-drug interactions using computational predictions. This study sought to identify common genetic pathways possibly involved in immune responses and cancer progression, providing a foundation for future targeted treatment research. The dataset comprises single nucleotide polymorphisms used as instrumental variables for Crohn's disease, analyzed to explore their possible impact on breast cancer risk. Gene ontology and pathway enrichment analyses were conducted to identify genes shared between the two conditions, supported by protein-protein interaction networks, colocalization analyses, and deep learning-based predictions of gene-drug interactions. The identified hub genes and predicted gene-drug interactions offer preliminary insights into possible therapeutic targets for breast cancer and immune-related conditions. This dataset may be valuable for researchers studying genetic links between autoimmune diseases and cancer and for those interested in the early identification of potential drug targets.

Indexed as

Breast cancerColocalizationCrohn’s diseaseDeep purposeGene-drug interactionsHub genesMendelian randomization

Identifiers

PMID39964572
PMCPMC11836263

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.