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Sabunciyan, S.

Publications and source records attributed to Sabunciyan, S..

3 recordsLinked to original sources

Differential Expression of NPAS4 in the Dorsolateral Prefrontal Cortex Following Acute Opioid Intoxication

Background and AimsThe physical, emotional, and social impacts of opioid abuse are well known; although preclinical models reveal the neurobiological pathways altered through opioid abuse, comprehensive assessments of gene expression in human brain samples are lacking. The goals of the present study were to compare gene expression in the prefrontal cortex between brain samples of individuals who died of acute opioid intoxication and group-matched controls, and to test if differential gene expression was enriched in gene sets related to opioid use. DesignCross-sectional study using human brains donated to the Lieber Institute for Brain Development. Study groups included 72 brain samples from individuals who died of acute opioid intoxication, 53 group-matched psychiatric control samples, and 28 group-matched normal control samples. SettingMaryland, USA. ParticipantsPostmortem tissue samples of the dorsolateral prefrontal cortex from 153 deceased individuals (Mage = 35.42, SD = 9.43 years; 62% male; 77% White). MeasurementsWhole transcriptome RNA sequencing was used to generate exon counts, and differential expression was tested using limma-voom. Analyses controlled for relevant sociodemographic characteristics, technical covariates, and cryptic relatedness and batch effects using quality surrogate variable analysis. Gene set enrichment analyses (GSEA) also were conducted. FindingsSixteen genes were differentially expressed (i.e., FDR-corrected p < .10) in opioid samples compared to control samples. The top differentially expressed gene, NPAS4 (FDR adjusted p = .005), was downregulated in opioid samples and has previously been implicated in cocaine use. Enrichment analyses did not provide evidence for enrichment in pathways obviously related to opioid use. ConclusionsNPAS4 is differentially expressed in the prefrontal cortex of subjects that died of an opioid overdose, providing evidence for another gene with functional relevance to opioid use and overdose.

genomics

Epigenome-wide study of brain DNA methylation among opioid users and controls

Opioid abuse poses significant risk to individuals in the United States and epigenetic changes are a leading potential biomarker of abuse. Current evidence, however, is mostly limited to candidate gene analysis in whole blood. To clarify the association between opioid abuse and DNA methylation, we conducted an epigenome-wide analysis (EWAS) of DNA methylation in brains of individuals who died from opioid intoxication and controls. Tissue samples were extracted from the dorsolateral prefrontal cortex of 160 deceased individuals (Mage = 35.15, SD = 9.42 years; 62% male; 78% White). The samples included 73 individuals who died of opioid intoxication, 59 group-matched psychiatric controls, and 28 group-matched normal controls. EWAS was implemented using the Illumina Infinium MethylationEPIC BeadChip; analyses adjusted for sociodemographic characteristics, negative control and ancestry principal components, cellular composition, and surrogate variables. Epigenetic age was calculated using the Horvath and Levine clocks, and gene ontology (GO) analyses were performed. No CpG sites were epigenome-wide significant after multiple testing correction, but 13 sites reached nominal significance (p < 1.0 x 10-5). There was a significant association between opioid use and Levine phenotypic age (b = 2.24, se = 1.11, p = .045). Opioid users were approximately two years phenotypically older compared to controls. GO analyses revealed enriched pathways related to cell function and neuron differentiation, but no terms survived multiple testing correction. Results inform our understanding of the neurobiology of opioid use, and future research with larger samples across stages of opioid use will elucidate the complex genomics of opioid abuse.

genomics

Comprehensive and scalable quantification of splicing differences with MntJULiP

Alternative splicing of mRNA is an essential gene regulatory mechanism with important roles in development and disease. We present MntJULiP, a method for comprehensive and accurate quantification of splicing differences between two or more conditions. MntJULiP implements novel Dirichlet-multinomial and zero-inflated negative binomial models within a Bayesian framework to detect both changes in splicing ratios and in absolute splicing levels of introns with high accuracy, and can find classes of variation overlooked by reference tools. Additionally, a mixture model allows multiple conditions to be compared simultaneously. Highly scalable, it processed hundreds of GTEx samples in <1 hour to reveal splicing constituents of tissue differentiation.

bioinformatics