Brain lncRNA-mRNA co-expression regulatory networks and alcohol use disorder

• Published in: Genomics (San Diego, Calif.) Vol. 116; no. 5; p. 110928
• Main Authors: Besong, Ojong Tabi Ojong, Koo, Ji Sun, Zhang, Huiping
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 01.09.2024
• Subjects: alcohol drinking; Alcohol use disorder; Alcoholism - genetics; Alcoholism - metabolism; alcohols; amygdala; ancestry; axons; Brain - metabolism; Brain reward circuitry; Female; Gene co-expression; gene expression regulation; Gene Regulatory Networks; genes; genomics; hippocampus; Human postmortem brain tissues; Humans; LncRNA-mRNA networks; Machine Learning; Male; neurodegenerative diseases; neuroplasticity; prefrontal cortex; RNA, Long Noncoding - genetics; RNA, Long Noncoding - metabolism; RNA, Messenger - genetics; RNA, Messenger - metabolism; rRNA depletion RNA-seq; sequence analysis; therapeutics; rRNA depletion RNA-seq; LncRNA-mRNA networks; Alcohol use disorder; Human postmortem brain tissues; Machine learning; Gene co-expression; Brain reward circuitry
• ISSN: 0888-7543; 1089-8646; 1089-8646
• DOI: 10.1016/j.ygeno.2024.110928

Prolonged alcohol consumption can disturb the expression of both coding and noncoding genes in the brain. These dysregulated genes may co-express in modules and interact within networks, consequently influencing the susceptibility to developing alcohol use disorder (AUD). In the present study, we performed an RNA-seq analysis of the expression of both long noncoding RNAs (lncRNAs) and messenger RNAs (mRNAs) in 192 postmortem tissue samples collected from eight brain regions (amygdala, caudate nucleus, cerebellum, hippocampus, nucleus accumbens, prefrontal cortex, putamen, and ventral tegmental area) of 12 AUD and 12 control subjects of European ancestry. Applying the limma-voom method, we detected a total of 57 lncRNAs and 51 mRNAs exhibiting significant differential expression (Padj < 0.05 and fold-change ≥2) across at least one of the eight brain regions investigated. Machine learning analysis further confirmed the potential of these top genes in predicting AUD. Through Weighted Gene Co-expression Network Analysis (WGCNA), we identified distinct lncRNA-mRNA co-expression modules associated with AUD in each of the eight brain regions. Additionally, lncRNA-mRNA co-expression networks were constructed for each brain region using Cytoscape to reveal gene regulatory interactions implicated in AUD. Hub genes within these networks were found to be enriched in several key KEGG pathways, including Axon Guidance, MAPK Signaling, p53 Signaling, Adherens Junction, and Neurodegeneration. Our results underscore the significance of networks involving AUD-associated lncRNAs and mRNAs in modulating neuroplasticity in response to alcohol exposure. Further elucidating these molecular mechanisms holds promise for the development of targeted therapeutic interventions for AUD. •Transcriptomic changes in lncRNAs and mRNAs were observed in multiple brain regions of subjects with alcohol use disorder.•Differentially expressed lncRNAs and mRNAs in the brain have the potential to predict alcohol use disorder.•LncRNAs and mRNAs are differentially co-expressed in multiple brain regions of subjects with alcohol use disorder.•LncRNAs and mRNAs co-expressed in alcohol use disorder-associated modules play roles in key pathways for neuroadaptation.