Opioid Use Disorder (OUD) is an ongoing worldwide public health concern. Genetic factors contribute to multiple OUD-related phenotypes, such as opioid-induced analgesia, initiation of opioid use, and opioid dependence. Here, we present findings from a behavioral phenotyping protocol using male and female rats from 15 genetically diverse inbred strains from the Hybrid Rat Diversity Panel (HRDP).
View Article and Find Full Text PDFIntroduction: Pregnant individuals who smoke face increased health risks because smoking harms both the mother and their developing offspring.
Methods: Using 307 417 Europeans from the UK Biobank, we examined whether exposure to maternal smoking during pregnancy (MSP) interacts with genetic risk to predict offspring birth weight (BW) and smoking behaviors. We investigated interactions between MSP and genetic risk at multiple levels: single variant, gene-level, and polygenic score.
A better understanding of nicotine neurobiology is needed to reduce or prevent chronic addiction, ameliorate the detrimental effects of nicotine withdrawal, and increase successful cessation of use. Nicotine binds and activates two astrocyte-expressed nicotinic acetylcholine receptors (nAChRs), α4β2 and α7. We recently found that ( or ) expression is restricted to astrocytes in mice and humans.
View Article and Find Full Text PDFOpioid use disorder (OUD) is an ongoing public health concern in the United States, and relatively little work has addressed how genetic background contributes to OUD. Understanding the genetic contributions to oxycodone-induced analgesia could provide insight into the early stages of OUD development. Here, we present findings from a behavioral phenotyping protocol using several inbred strains from the Hybrid Rat Diversity Panel.
View Article and Find Full Text PDFBackground: The understanding of the molecular genetic contributions to smoking is largely limited to the additive effects of individual single nucleotide polymorphisms (SNPs), but the underlying genetic risk is likely to also include dominance, epistatic, and gene-environment interactions.
Methods: To begin to address this complexity, we attempted to identify genetic interactions between rs16969968, the most replicated SNP associated with smoking quantity, and all SNPs and genes across the genome.
Results: Using the UK Biobank European subsample, we found one SNP, rs1892967, and two genes, PCNA and TMEM230, that showed a significant genome-wide interaction with rs16969968 for log10 CPD and raw CPD, respectively, in a sample of 116 442 individuals who self-reported currently or previously smoking.