Male mice exposed to chronic intermittent ethanol exposure exhibit significant upregulation or downregulation of circular RNAs

Orbitofrontal intronic circular RNA from Nrxn3 mediates reward learning and motivation for reward

The orbitofrontal cortex (OFC) is a vital component of brain reward circuitry that is important for reward seeking behavior. However, OFC-mediated molecular mechanisms underlying rewarding behavior are understudied. Here, we report the first circular RNA (circRNA) profile associated with appetitive reward and identify regulation of 92 OFC circRNAs by sucrose self-administration. Among these changes, we observed downregulation of circNrxn3, a circRNA originating from neurexin 3 (Nrxn3), a gene involved in synaptogenesis, learning, and memory. Transcriptomic profiling via RNA sequencing and qPCR of the OFC following in vivo knock-down of circNrxn3 revealed differential regulation of genes associated with pathways important for learning and memory and altered splicing of Nrxn3. Furthermore, circNrxn3 knock-down enhanced sucrose self-administration and motivation for sucrose. Using RNA-immunoprecipitation, we report binding of circNrxn3 to the known Nrxn3 splicing factor SAM68. circNrxn3 is the first reported circRNA capable of regulating reward behavior and circNrxn3-mediated interactions with SAM68 may impact subsequent downstream processing of RNAs such as the regulation of gene expression and splicing.

Circular RNA regulation and function in drug seeking phenotypes

Drug overdoses have increased dramatically in the United States over the last decade where they are now the leading cause of accidental death. To develop efficient therapeutic options for decreasing drug consumption and overdose risk, it is critical to understand the neurobiological changes induced by drug exposure. Chronic systemic exposure to all drug classes, including opioids, psychostimulants, nicotine, cannabis, and alcohol, induces profound molecular neuroadaptations within the central nervous system that may reveal crucial information about the lasting effects that these substances impart on brain cells. Transcriptome analyses of messenger RNAs (mRNAs) have identified gene patterns in the brain that result from exposure to various classes of drugs. However, mRNAs represent only a small fraction of the RNA within the cell, and drug exposure also impacts other classes of RNA that are largely understudied, especially circular RNAs. Circular RNAs (circRNAs) are a naturally occurring RNA species formed from back-splicing events during mRNA processing and are enriched in the nervous system. circRNAs are a pleiotropic class of RNAs and have a diverse impact on cellular function, with putative functions including regulation of mRNA transcription, protein translation, microRNA sponging, and sequestration of RNA-binding proteins. Recent studies have demonstrated that circRNAs can modulate cognition and are regulated in the brain in response to drug exposure, yet very few studies have explored the contribution of circRNAs to drug seeking phenotypes. In this review, we will provide an overview of the mechanisms of circRNA function in the cell to highlight how drug-induced circRNA dysregulation may impact the molecular substrates that mediate drug seeking behavior and the current studies that have reported drug-induced dysregulation of circRNAs in the brain. Furthermore, we will discuss how principles of circRNA biology can be adapted to study circRNAs in models of drug exposure and seek to provide further insight into the neurobiology of addiction.

RNA biomarkers for alcohol use disorder

Alcohol use disorder (AUD) is highly prevalent and one of the leading causes of disability in the US and around the world. There are some molecular biomarkers of heavy alcohol use and liver damage which can suggest AUD, but these are lacking in sensitivity and specificity. AUD treatment involves psychosocial interventions and medications for managing alcohol withdrawal, assisting in abstinence and reduced drinking (naltrexone, acamprosate, disulfiram, and some off-label medications), and treating comorbid psychiatric conditions (e.g., depression and anxiety). It has been suggested that various patient groups within the heterogeneous AUD population would respond more favorably to specific treatment approaches. For example, there is some evidence that so-called reward-drinkers respond better to naltrexone than acamprosate. However, there are currently no objective molecular markers to separate patients into optimal treatment groups or any markers of treatment response. Objective molecular biomarkers could aid in AUD diagnosis and patient stratification, which could personalize treatment and improve outcomes through more targeted interventions. Biomarkers of treatment response could also improve AUD management and treatment development. Systems biology considers complex diseases and emergent behaviors as the outcome of interactions and crosstalk between biomolecular networks. A systems approach that uses transcriptomic (or other -omic data, e.g., methylome, proteome, metabolome) can capture genetic and environmental factors associated with AUD and potentially provide sensitive, specific, and objective biomarkers to guide patient stratification, prognosis of treatment response or relapse, and predict optimal treatments. This Review describes and highlights state-of-the-art research on employing transcriptomic data and artificial intelligence (AI) methods to serve as molecular biomarkers with the goal of improving the clinical management of AUD. Considerations about future directions are also discussed.