A comprehensive RNA-sequencing analysis of postmortem nucleus accumbens tissue from individuals with OUD and matched controls provides an integrated view of candidate genetic and transcriptomic alterations in OUD and identifies lncRNA-centered regulatory networks and candidate variant-bearing genes as hypothesis-generating leads for future functional and DNA-based validation studies.
Abstract
Introduction Opioid Use Disorder (OUD) is a chronic condition characterized by compulsive opioid intake that drives widespread health, social, and economic burdens. Methods To elucidate molecular contributors to addiction susceptibility, we conducted a comprehensive RNA-sequencing analysis of postmortem nucleus accumbens (NAc) tissue from individuals with OUD and matched controls. Results Cohort-concordance filtering identified 17 candidate missense variants and one candidate stop-gain variant across 16 genes detected in OUD samples; these RDEVs require DNA-based validation. Missense variants could disrupt key protein domains, and five of these identified variants (FUT9, FMR1, MFN1, RYR3, and DAG1) have been previously linked to Substance Use Disorders (SUDs) traits. The only stop-gain variant, ZNF117, was predicted to produce a truncated protein via impaired folding. Transcriptomic profiling followed by Ingenuity Pathway Analysis (IPA) predicted activation of neurodevelopmental programs, with 145 upregulated and 29 downregulated genes collectively implicating pathways related to synaptic plasticity, neuronal differentiation, and axon guidance. Importantly, differential expression of long non-coding RNAs (lncRNAs), including LINC01554 and LINC00996, was identified, with putative regulatory associations with key transcription factors (TFs) such as NPAS4 and GADD45B. Discussion Together, these findings provide an integrated view of candidate genetic and transcriptomic alterations in OUD and identify lncRNA-centered regulatory networks and candidate variant-bearing genes as hypothesis-generating leads for future functional and DNA-based validation studies.
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