Genomic Insights into Opioid Addiction: Identification of genomic variants from Gene Expression data
Discuss this preprint
Start a discussion What are Sciety discussions?Listed in
This article is not in any list yet, why not save it to one of your lists.Abstract
Background
Next-generation sequencing (NGS) has transformed high-throughput DNA and RNA analysis, facilitating the rapid identification of clinically relevant genetic variants. Opioid Use Disorder (OUD), a chronic condition characterized by relapse and remission cycles, poses significant challenges for genomic investigations. While whole-exome sequencing (WES) and whole-genome sequencing (WGS) serve as robust approaches for variant detection, their high cost restricts widespread use. RNA sequencing (RNA-Seq) presents a viable alternative; however, the complexity of the transcriptome complicates reliable variant identification. Despite these challenges, RNA-Seq has emerged as a valuable tool for detecting single nucleotide polymorphisms (SNPs) in conditions with limited WES data, such as OUD.
Methods
In this study, RNA-Seq data from postmortem ventral midbrain specimens of chronic opioid users (PRJNA492904) were analyzed to identify variants associated with OUD. Given its established involvement in opioid addiction and impulsivity, we hypothesized that the NRXN3 gene would harbor a significant number of variants. Variant analysis was conducted across eight genes: BDNF, DRD2, DRD3, NRXN3, OPRD1, OPRM1, and NGFB —with a primary focus on NRXN .
Results
Our results revealed that NRXN3 exhibited the highest variant burden among the analyzed genes, highlighting its potential role in OUD pathogenesis and reinforcing its association with opioid addiction.
Conclusion
Our study highlights the significance of transcriptomic variant analysis in opioid addiction and underscores the potential of NRXN3 variants as biomarkers or therapeutic targets, warranting further investigation.
