Transcriptomic analysis reveals the crosstalk between type 2 diabetes and chronic pancreatitis.

Autor: Chen, Youlan, Hao, Lixiao, Cong, Jun, Ji, Jianmei, Dai, Yancheng, Xu, Li, Gong, Biao
Předmět:
Zdroj: Health Science Reports; May2024, Vol. 7 Issue 5, p1-13, 13p
Abstrakt: Background and Aims: Mounting evidence highlights a strong association between chronic pancreatitis (CP) and type 2 diabetes (T2D), although the exact mechanism of interaction remains unclear. This study aimed to investigate the crosstalk genes and pathogenesis between CP and T2D. Methods: Transcriptomic gene expression profiles of CP and T2D were extracted from Gene Expression Omnibus, respectively, and the common differentially expressed genes (DEGs) were subsequently identified. Further analysis, such as Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), protein–protein interaction, transcription factors (TFs), microRNA (miRNAs), and candidate chemicals identification, was performed to explore the possible common signatures between the two diseases. Results: In total, we acquired 281 common DEGs by interacting CP and T2D datasets, and identified 10 hub genes using CytoHubba. GO and KEGG analyses revealed that endoplasmic reticulum stress and mitochondrial dysfunction were closely related to these common DEGs. Among the shared genes, EEF2, DLD, RAB5A, and SLC30A9 showed promising diagnostic value for both diseases based on receiver operating characteristic curve and precision‐recall curves. Additionally, we identified 16 key TFs and 16 miRNAs that were strongly correlated with the hub genes, which may serve as new molecular targets for CP and T2D. Finally, candidate chemicals that might become potential drugs for treating CP and T2D were screened out. Conclusion: This study provides evidence that there are shared genes and pathological signatures between CP and T2D. The genes EEF2, DLD, RAB5A, and SLC30A9 have been identified as having the highest diagnostic efficiency and could be served as biomarkers for these diseases, providing new insights into precise diagnosis and treatment for CP and T2D. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index