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Unveiling Common Molecular Signatures and Pathways in Psychiatric Disorders and Alcohol Use Disorder through Integrated Transcriptome Analysis

Created on 07 Mar 2026

Authors

Khan, M., Khan, S., Amin, M. F., Hossain, M. A.

Abstract

Research studies have demonstrated that persons who have Alcohol Use Disorder (AUD) exhibit a more severe progression of psychiatric disorders, indicating potential causal connections between AUD and psychiatric disorders. Identifying underlying risk variables between AUD and psychiatric problems continues to be challenging. To address these issues, we created a bioinformatics pipeline and employed network-based methods to discover genes that exhibit improper expression in both AUD and psychiatric disorders. The objective of our study was to identify common molecular pathways that may elucidate the relationship between AUD and psychiatric disorders. We identified 49 genes that were expressed differently in tissue samples of patients with both AUD and psychiatric disorders. The DAVID online platform was used to discover the most significant Gene Ontology (GO) keywords and metabolic pathways. It detected the involvement of immune response, chemokine activity, TNF signaling, IL 17 signaling, and prostaglandin signaling pathways among the common DEGs. In addition, eleven topological algorithms identified a single hub protein, specifically TTR, from the protein-protein interaction (PPI) network. Through regulatory network analysis, we identified four crucial transcription factors (TFs)YY1, FOXC1, JUND, and GATA2 and seven miRNAs (e.g., hsa-mir-146a-5p, hsa-mir-20a-5p) that play vital roles in regulating the development of AUD and psychiatric disorders. These miRNAs may serve as potential therapeutic targets. Validation of the hub gene using ROC analysis indicated acceptable predictive performance. Our approach revealed several potential biomarkers and signaling pathways linking AUD with psychiatric disorders, offering new insights for diagnosis and treatment.

Preprint server: bioRxiv
The authors list and abstract were imported from bioRxiv on 07 Mar 2026.

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