Biology subjects

Ehringer, M. A.

Publications and source records attributed to Ehringer, M. A..

4 recordsLinked to original sources

bioRxiv2024

Sex and genetic background influence intravenous oxycodone self-administration in the Hybrid Rat Diversity Panel

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). We used a self-administration paradigm to measure the acquisition of oxycodone intake during ten 2-hour sessions and escalation of oxycodone use during ten 12-hour sessions. During both the acquisition and escalation phases of self-administration, we observed that genetic background and sex influence oxycodone intake. The heritability of oxycodone intake phenotypes ranged between 0.26 to 0.54, indicating that genetic background plays a major role in the variability of oxycodone consumption. Genetic background and sex also influenced additional phenotypes recorded during oxycodone self-administration including lever discrimination and timeout responding. The genetic contribution to these traits was slightly more moderate, with heritability estimates ranging between 0.25 to 0.42. Measures of oxycodone intake were highly positively correlated between acquisition and escalation phases. Interestingly, the efficacy of oxycodone analgesia was positively correlated with oxycodone intake during the escalation phase, indicating that the initial behavioral responses to oxycodone may predict self-administration phenotypes. Together, these data demonstrate that sex and genetic background are major contributors to oxycodone self-administration phenotypes.

genetics↗

bioRxiv2024

AKT2 modulates astrocytic nicotine responses in vivo.

A greater understanding of the neurobiology of nicotine is needed to reduce or prevent chronic addiction, ameliorate detrimental nicotine withdrawal effects, and improve cessation rates. Nicotine binds and activates two astrocyte-expressed nicotinic acetylcholine receptors (nAChRs), 4{beta}2 and 7. Protein kinase B-{beta} (Pkb-{beta} or Akt2) expression is restricted to astrocytes in mice and humans and is activated by nicotine. To determine if AKT2 plays a role in astrocytic nicotinic responses, we generated astrocyte-specific Akt2 conditional knockout (cKO) and full Akt2 KO mice. For in/ex vivo studies, we examined mice exposed to chronic nicotine for two weeks in drinking water (200 g/mL) or following acute nicotine challenge (0.09, 0.2 mg/kg) after 24 hrs. Our in vitro studies used cultured mouse astrocytes to measure nicotine-dependent astrocytic responses. Sholl analysis was used to measure glial fibrillary acidic protein responses in astrocytes. Our data show wild-type (WT) mice exhibit increased astrocyte morphological complexity during acute nicotine exposure, with decreasing complexity during chronic nicotine use, whereas Akt2 cKO mice showed enhanced acute responses and reduced area following chronic exposure. In culture, we found 100 M nicotine sufficient for morphological changes and blocking 7 or 4{beta}2 nAChRs prevented observed morphologic changes. We performed conditioned place preference (CPP) in Akt2 cKO mice, which revealed reduced nicotine preference in cKO mice compared to controls. Finally, we performed RNASeq comparing nicotine- and LPS-mediated gene expression, identifying robust differences between these two astrocytic stimuli. These findings show the importance of nAChRs and AKT2 signaling in the astrocytic response to nicotine. Main PointsO_LINicotine regulates astrocytes in vivo: acute exposure boosts complexity; chronic exposure diminishes it. C_LIO_LIAKT2, expressed in astroglia, modulates morphological changes in response to nicotine and nicotine-dependent conditioned place preference. C_LI

neuroscience↗

bioRxiv2022

Transcriptome-Wide Gene-Gene Interaction Association Study Elucidates Pathways and Functional Enrichment of Complex Traits

It remains unknown to what extent gene-gene interactions contribute to complex traits. Here, we introduce a new approach using predicted gene expression to perform exhaustive transcriptome-wide interaction studies (TWISs) for multiple traits across all pairs of genes expressed in several tissue types. Using imputed transcriptomes, we simultaneously reduce the computational challenge and improve interpretability and statistical power. We discover and replicate several interaction associations, and find several hub genes with numerous interactions. We also demonstrate that TWIS can identify novel associated genes because genes with many or strong interactions have smaller single-locus model effect sizes. Finally, we develop a method to test gene set enrichment of TWIS associations (E-TWIS), finding numerous pathways and networks enriched in interaction associations. Epistasis is likely widespread, and our procedure represents a tractable framework for beginning to explore gene interactions and identify novel genomic targets.

genetics↗

bioRxiv2022

Testing Human Anxiety Associations of Genes Previously Implicated by Mouse Anxiety Models

Anxiety disorders are common and can be debilitating, with effective treatments remaining hampered by an incomplete understanding of the underlying genetic etiology. Improvements have been made in understanding the genetic influences on mouse behavioral models of anxiety, yet it is unclear the extent to which genes identified in these experimental systems contribute to genetic variation in human anxiety phenotypes. Leveraging new and existing large-scale human genome-wide association studies, we tested whether sets of genes previously identified in mouse anxiety-like behavior studies contribute to a range of human anxiety disorders. When tested as individual genes, thirteen mouse-identified genes were associated with human anxiety phenotypes, suggesting an overlap of individual genes contributing to both mouse models of anxiety-like behaviors and human anxiety traits. When genes were tested as sets, we did identify fourteen significant associations between mouse gene sets and human anxiety, but the majority of gene sets showed no significant association with human anxiety phenotypes. These few significant associations indicate a need to identify and develop more translatable mouse models by identifying sets of genes that match between model systems and specific human phenotypes of interest. We suggest that continuing to develop improved behavioral paradigms and finer-scale experimental data, for instance from individual neuronal subtypes or cell-type-specific expression data, is likely to improve our understanding of the genetic etiology and underlying functional changes in anxiety disorders.

genetics↗