Cerebellar Transcriptomic Analysis in a Chronic plus Binge Mouse Model of Alcohol Use Disorder Demonstrates Ethanol-Induced Neuroinflammation and Altered Glial Gene Expression.
Kalee N HollowayMarisa R PinsonJames C DouglasTonya M RaffertyCynthia J M KaneRajesh R MirandaPaul D DrewPublished in: Cells (2023)
Alcohol use disorder (AUD) is one of the most common preventable mental health disorders and can result in pathology within the CNS, including the cerebellum. Cerebellar alcohol exposure during adulthood has been associated with disruptions in proper cerebellar function. However, the mechanisms regulating ethanol-induced cerebellar neuropathology are not well understood. High-throughput next generation sequencing was performed to compare control versus ethanol-treated adult C57BL/6J mice in a chronic plus binge model of AUD. Mice were euthanized, cerebella were microdissected, and RNA was isolated and submitted for RNA-sequencing. Down-stream transcriptomic analyses revealed significant changes in gene expression and global biological pathways in control versus ethanol-treated mice that included pathogen-influenced signaling pathways and cellular immune response pathways. Microglial-associated genes showed a decrease in homeostasis-associated transcripts and an increase in transcripts associated with chronic neurodegenerative diseases, while astrocyte-associated genes showed an increase in transcripts associated with acute injury. Oligodendrocyte lineage cell genes showed a decrease in transcripts associated with both immature progenitors as well as myelinating oligodendrocytes. These data provide new insight into the mechanisms by which ethanol induces cerebellar neuropathology and alterations to the immune response in AUD.
Keyphrases
- alcohol use disorder
- single cell
- gene expression
- immune response
- high throughput
- drug induced
- mental health
- rna seq
- high fat diet induced
- genome wide
- mouse model
- dna methylation
- high glucose
- diabetic rats
- signaling pathway
- genome wide identification
- bioinformatics analysis
- traumatic brain injury
- machine learning
- depressive symptoms
- lipopolysaccharide induced
- lps induced
- cell therapy
- stem cells
- electronic health record
- toll like receptor
- epithelial mesenchymal transition
- brain injury
- candida albicans
- adipose tissue
- oxidative stress
- artificial intelligence
- deep learning
- endoplasmic reticulum stress
- acute respiratory distress syndrome
- hepatitis b virus
- mechanical ventilation