Evidence map›Paper›PMID 41595424›Full record

ArticleGenes2025

Machine Learning Reveals Common Regulatory Mechanisms Mediated by Autophagy-Related Genes in the Development of Inflammatory Bowel Disease and Major Depressive Disorder.

Gengxian Wang, Luojin Wu, Jiyuan Shi, Mengmeng Sang, Liming Mao

Abstract read
In one paragraph

Article in Genes, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Gengxian WangSchool of Life Science and Engineering, Handan University, Handan 056005, China.
Luojin WuDepartment of Immunology, School of Medicine, Nantong University, Nantong 226001, China.
Jiyuan ShiDepartment of Immunology, School of Medicine, Nantong University, Nantong 226001, China.
Mengmeng SangDepartment of Immunology, School of Medicine, Nantong University, Nantong 226001, China.ORCID 0000-0001-5249-002X
Liming MaoDepartment of Immunology, School of Medicine, Nantong University, Nantong 226001, China.ORCID 0000-0002-9740-820X

Funding

National Natural Science Foundation of China 32270919
6 · The paper itself

Abstract

backgroundMajor Depressive Disorder (MDD) is more common in patients with Inflammatory Bowel Disease (IBD) than in the general population, suggesting a shared but unclear pathogenesis. Autophagy, a conserved intracellular cleaning process, maintains cellular health by removing debris and recycling nutrients. Given the limited research on autophagy in this comorbidity, this study investigated the role of autophagy-related genes in both disorders.

aimThis study aimed to identify shared autophagy-related mechanisms between IBD and MDD and to explore potential therapeutic strategies.

methodsWe identified differentially expressed autophagy-related genes (DE-ARGs) in diseased versus normal tissues. Shared DE-ARGs between IBD and MDD were designated Co-DEGs. We analyzed correlations among Co-DEGs and their association with immune cell infiltration. Four machine-learning algorithms were used to pinpoint key biomarkers. Potential therapeutic agents were predicted and validated via molecular docking.

resultsWe identified 47 shared Co-DEGs. Among these,

conclusionsOur findings illuminate autophagy-mediated mechanisms linking gut and brain disorders. The identification of

Indexed as

AutophagyAutophagy-Related ProteinsInflammatory Bowel DiseasesMachine LearningMajor Depressive DisorderGenetic Predisposition to DiseaseHumansMolecular Docking SimulationAutophagy-Related Proteinsautophagyinflammatory bowel diseasemachine learning algorithmmajor depressive disordermolecular docking and dynamics analysis

Identifiers

PMID41595424
PMCPMC12841238

What Socratic 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 Socratic graph.