Evidence map›Paper›PMID 38429902›Full record

ArticleJournal of cellular and molecular medicine2024

Identification of crosstalk genes relating to ECM-receptor interaction genes in MASH and DN using bioinformatics and machine learning.

Chao Chen, Yuxi He, Ying Ni, Zhanming Tang, Wensheng Zhang

Open access · goldAbstract read
In one paragraph

Article in Journal of cellular and molecular medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.3field-weighted citation impact, top 49% of its field
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

4 citing papers in PubMed, 1 citations in OpenAlex.

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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 at 2 institutions in 1 country.

Chao ChenInstrumentation and Service Center for Science and Technology, Beijing Normal University, Zhuhai, China.ORCID 0000-0003-3958-2805
Yuxi HePediatric Research Institute, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, China.
Ying NiZhuhai Branch of State Key Laboratory of Earth Surface Processes and Resource Ecology, Advanced Institute of Natural Sciences, Beijing Normal University, Zhuhai, China.
Zhanming TangZhuhai Branch of State Key Laboratory of Earth Surface Processes and Resource Ecology, Advanced Institute of Natural Sciences, Beijing Normal University, Zhuhai, China.
Wensheng ZhangZhuhai Branch of State Key Laboratory of Earth Surface Processes and Resource Ecology, Advanced Institute of Natural Sciences, Beijing Normal University, Zhuhai, China.
Beijing Normal University · CNWenzhou Medical University · CN

Funding

National Nature Science Foundation of China 81771152
6 · The paper itself

Abstract

This study aimed to identify genes shared by metabolic dysfunction-associated fatty liver disease (MASH) and diabetic nephropathy (DN) and the effect of extracellular matrix (ECM) receptor interaction genes on them. Datasets with MASH and DN were downloaded from the Gene Expression Omnibus (GEO) database. Pearson's coefficients assessed the correlation between ECM-receptor interaction genes and cross talk genes. The coexpression network of co-expression pairs (CP) genes was integrated with its protein-protein interaction (PPI) network, and machine learning was employed to identify essential disease-representing genes. Finally, immuno-penetration analysis was performed on the MASH and DN gene datasets using the CIBERSORT algorithm to evaluate the plausibility of these genes in diseases. We found 19 key CP genes. Fos proto-oncogene (FOS), belonging to the IL-17 signalling pathway, showed greater centrality PPI network; Hyaluronan Mediated Motility Receptor (HMMR), belonging to ECM-receptor interaction genes, showed most critical in the co-expression network map of 19 CP genes; Forkhead Box C1 (FOXC1), like FOS, showed a high ability to predict disease in XGBoost analysis. Further immune infiltration showed a clear positive correlation between FOS/FOXC1 and mast cells that secrete IL-17 during inflammation. Combining the results of previous studies, we suggest a FOS/FOXC1/HMMR regulatory axis in MASH and DN may be associated with mast cells in the acting IL-17 signalling pathway. Extracellular HMMR may regulate the IL-17 pathway represented by FOS through the Mitogen-Activated Protein Kinase 1 (ERK) or PI3K-Akt-mTOR pathway. HMMR may serve as a signalling carrier between MASH and DN and could be targeted for therapeutic development.

Indexed as

Diabetic NephropathiesInterleukin-17Computational BiologyHumansMachine LearningPhosphatidylinositol 3-KinasesInterleukin-17Phosphatidylinositol 3-KinasesDNECM-receptor interactionimmune infiltrationMASHXGBoost

Identifiers

PMID38429902
PMCPMC10907849
OpenAlexW4392346260

What OpenQuestion holds

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LicenceCC BY
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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.