Evidence map›Paper›PMID 42137128›Full record

ArticleGastroenterology and hepatology from bed to bench2025

A bioinformatics analysis to identify shared molecular pathways and hub genes between NAFLD and Gestational Diabetes Mellitus.

Nasrin Amiri-Dashatan, Mehdi Koushki, Masoumeh Farahani, Somayeh Chahkandi, Mohammad Salehi, Hossein Chiti, Zohreh Amarloo, Aliasghar Keramatinia, Mohsen Norouzinia

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Article in Gastroenterology and hepatology from bed to bench, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Nasrin Amiri-DashatanZanjan Metabolic Diseases Research Center, Health and Metabolic Diseases Research Institute, Zanjan University of Medical Sciences, Zanjan, Iran.
Mehdi KoushkiCancer Gene Therapy Research Center, Zanjan University of Medical Sciences, Zanjan, Iran.
Masoumeh FarahaniProteomics Research Center, Faculty of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Somayeh ChahkandiZanjan Metabolic Diseases Research Center, Health and Metabolic Diseases Research Institute, Zanjan University of Medical Sciences, Zanjan, Iran.
Mohammad SalehiDepartment of Clinical Biochemistry, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, Iran.
Hossein ChitiZanjan Metabolic Diseases Research Center, Health and Metabolic Diseases Research Institute, Zanjan University of Medical Sciences, Zanjan, Iran.
Zohreh AmarlooDepartment of Clinical Biochemistry, School of Medicine, Zanjan University of Medical Sciences, Zanjan, Iran.
Aliasghar KeramatiniaDepartment of Community Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Mohsen NorouziniaGastroenterology and Liver Diseases Research Center, Research Institute for Gastroenterology and Liver Diseases, Shahid Beheshti University of Medical Sciences, Tehran, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Aim: This research aimed to identify the possible links between Non-alcoholic fatty liver disease (NAFLD) and gestational diabetes mellitus (GDM) by examining shared genes and pathways through the use of bioinformatics tools. Background: NAFLD presents several potential risk factors for the onset of GDM. Methods: We downloaded relevant microarray datasets from the Gene Expression Omnibus (GEO) database for screening common differentially expressed genes (DEGs) between NAFLD and GDM by GEO2R. Then, we used gene ontology analysis to explore the biological processes and KEGG pathways of NAFLD and GDM occurrence. The hub genes of each disease were screened by analysis of the PPI network, and the common hub genes were identified. We designed a co-expression network and miRNA hub gene regulatory network for selected hub genes by using GeneMANIA and miRNet platforms, respectively. Results: We identified 521 and 185 DEGs for NAFLD and GDM, respectively. 10 shared genes (FOS, CD22, AMZ1, ANGPT2, ATP1B2, STAB2, EGR1, MMP9, CXCL9, and LCN2) were screened among DEGs of two diseases, with analysis revealing enrichment in pathways such as IL-7 and TNF signaling pathways. Then, common hub genes (FOS, MMP9, and CXCL9) were identified via PPI network analysis, which were strongly correlated with both diseases. In addition, has-mir-34a-5p and has-mir-335-5p were detected as shared miRs that target hubs. Conclusion: We found 3 shared hub genes involved in NAFLD and GDM. Our research established a connection between the two diseases and could aid in formulating possible intervention strategies aimed at addressing both disorders by utilizing these risk factors.

Indexed as

BioinformaticsGestational diabetes mellitusNon-alcoholic fatty liver diseaseProtein-protein interaction networkShared genes

Identifiers

PMID42137128
PMCPMC13081419

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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.