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Cannella, N.

Publications and source records attributed to Cannella, N..

5 recordsLinked to original sources

Genomic SEM reveals shared genetic architecture and expands locus discovery for locomotor activity in heterogeneous stock rats

Locomotor response to a novel environment is a heritable, addiction-relevant behavioral phenotype in rodents. We characterized its genetic basis in 9,341 male and female heterogeneous stock (HS) rats from eight studies. Locomotor activity was heritable across studies, while pairwise genetic correlations were positive but variable, indicating shared yet nonidentical genetic influences. Given nonuniform genetic architecture, we compared three complementary approaches to locus discovery that analyzed SNP effects 1) on a pooled locomotor phenotype (MEGA), 2) across studies under a fixed-effect model (METAL), or 3) on a shared genetic factor (Genomic SEM). To ensure comparability, all three locus-discovery approaches were applied to a common subset of seven studies. Together, these approaches identified 38 loci, with both convergence and method-specific discovery across analyses. Genomic SEM identified 31 loci, compared to 8 for MEGA and 13 for METAL. To interpret the loci, we integrated brain molecular QTLs, predicted coding and splice consequences, and open-field locomotor phenotypes from knockouts of orthologous mouse genes. Our results highlighted established neurobehavioral candidates spanning locomotor and reward-related biology (Negr1 and Lmo4), serotonergic signaling (Htr1b), and GABAergic signaling (Gabrg2), as well as relatively novel genes including Tcerg1l, Pcdh10, and Tmem132e. Our results illustrate how Genomic SEM can integrate genetically correlated yet heterogeneous behavioral measures and enable discovery of loci underlying their shared genetic architecture, highlighting its utility for complex-trait studies in rodents.

genetics↗

Long-access heroin self-administration induces region specific reduction of grey matter volume and microglia reactivity in the rat.

In opioid use disorder (OUD) patients, a decrease in brain grey matter volume (GMV) has been reported. It is unclear whether this is the consequence of prolonged exposure to opioids or is a predisposing causal factor in OUD development. To investigate this, we conducted a structural MRI longitudinal study in NIH Heterogeneous Stock rats exposed to heroin self-administration and age-matched naive controls housed in the same controlled environment. Structural MRI scans were acquired before (MRI1) and after (MRI2) a prolonged period of long access heroin self-administration resulting in escalation of drug intake. Heroin intake resulted in reduced GMV in various cortical and sub-cortical brain regions. In drug-naive controls no difference was found between MRI1 and MRI2. Notably, the degree of GMV reduction in the medial prefrontal cortex (mPFC) and the insula positively correlated with the amount of heroin consumed and the escalation of heroin use. In a preliminary gene expression analysis, we identified a number of transcripts linked to immune response and neuroinflammation. This prompted us to hypothesize a link between changes in microglia homeostasis and loss of GMV. For this reason, we analyzed the number and morphology of microglial cells in the mPFC and insula. The number of neurons and their morphology was also evaluated. The primary motor cortex, where no GMV change was observed, was used as negative control. We found no differences in the number of neurons and microglia cells following heroin. However, in the same regions where reduced GMV was detected, we observed a shift towards a rounder shape and size reduction in microglia, suggestive of their homeostatic change towards a reactive state. Altogether these findings suggest that escalation of heroin intake correlates with loss of GMV in specific brain regions and that this phenomenon is linked to changes in microglial morphology.

neuroscience↗

A multi-symptomatic model of heroin use disorder in rats reveals distinct behavioral profiles and neuronal correlates of heroin vulnerability versus resiliency

ObjectiveThe behavioral and diagnostic heterogeneity within human opioid use disorder (OUD) diagnosis is not readily captured in current animal models, limiting translational relevance of the mechanistic research that is conducted in experimental animals. We hypothesize that a non-linear clustering of OUD-like behavioral traits will capture population heterogeneity and yield subpopulations of OUD vulnerable rats with distinct behavioral and neurocircuit profiles. MethodsOver 900 male and female heterogeneous stock rats, a line capturing genetic and behavioral heterogeneity present in humans, were assessed for several measures of heroin use and rewarded and non-rewarded seeking behaviors. Using a non-linear stochastic block model clustering analysis, rats were assigned to OUD vulnerable, intermediate and resilient clusters. Additional behavioral tests and circuit analyses using c-fos protein activation were conducted on the vulnerable and resilient subpopulations. ResultsOUD vulnerable rats exhibited greater heroin taking and seeking behaviors relative to those in the intermediate and resilient clusters. Akin to human OUD diagnosis, further vulnerable rat sub-clustering revealed subpopulations with different combinations of behavioral traits, including sex differences. Lastly, heroin cue-induced neuronal patterns of circuit activation differed between resilient and vulnerable phenotypes. Behavioral sex differences were recapitulated in patterns of circuitry activation, including males preferentially engaging extended amygdala stress circuitry, and females cortico-striatal drug cue-seeking circuitry. ConclusionUsing a non-linear clustering approach in rats, we captured behavioral diagnostic heterogeneity reflective of human OUD diagnosis. OUD vulnerability and resiliency were associated with distinct neuronal activation patterns, posing this approach as a translational tool in assessing neurobiological mechanisms underpinning OUD.

neuroscience↗

Cebranopadol, a novel long-acting opioid agonist with low abuse liability, to treat opioid use disorder: Preclinical evidence of efficacy

The gold standard pharmacological treatment for opioid use disorder (OUD) consists of maintenance therapy with long-acting opioid agonists such as buprenorphine and methadone. Despite these compounds having demonstrated substantial efficacy, a significant number of patients do not show optimal therapeutic responses. Moreover, the abuse liability of these medications remains a major concern. Cebranopadol, is a new, long-acting pan-opioid agonist that also activates the nociception/orphanin FQ NOP receptor. Here we used rats to explore the therapeutic potential of this agent in OUD. First, in operant intravenous self-administration experiments we compared the potential abuse liability of cebranopadol with the prototypical opioid heroin. Under a fixed ratio 1 (FR1) contingency, rats maintained responding for heroin (1, 7, 20, 60 g/inf) to a larger extent than cebranopadol (0.03, 0.1, 0.3, 1.0, 6.0 g/inf). When the contingency was switched to a progressive ratio (PR) reinforcement schedule, heroin maintained responding at high levels at all except the lowest dose. Conversely, in the cebranopadol groups responding decreased drastically and the break point (BP) did not differ from saline controls. Next, we demonstrated that oral administration of cebranopadol (0, 25, 50 g/kg) significantly attenuated drug self-administration independent of heroin dose (1, 7, 20, 60 g/inf). Cebranopadol also reduced the break point for heroin (20 g/inf). Furthermore, in a heroin self-administration training extinction/reinstatement paradigm, pretreatment with cebranopadol significantly attenuated yohimbine stress-induced reinstatement of drug seeking. Together, these data indicate that cebranopadol has limited abuse liability compared to heroin and is highly efficacious in attenuating opioid self-administration and stress-induced reinstatement, suggesting clinical potential of this compound for OUD treatment.

pharmacology and toxicology↗

Network-Based Discovery of Opioid Use Vulnerability in Rats Using the Bayesian Stochastic Block Model

Opioid use disorder is a psychological condition that affects over 200,000 people per year in the U.S., causing the Centers for Disease Control and Prevention to label the crisis as a rapidly spreading public health epidemic. It has been found that the behavioral relationship between opioid exposure and development of opioid use disorder varies greatly between individuals, implying existence of sup-populations with varying degrees of opioid vulnerability. In this study, we assessed several behavioral variables across heroin taking, refraining and seeking to establish how these factors interact with one another resulting in a heroin dependent, resilient, or vulnerable behavioral phenotype. Over 400 (male and female) heterogeneous stock rats were used in these two studies, and data were collected from two geographically distinct locations. Rats underwent heroin self-administration training, followed by a progressive ratio and heroin-primed reinstatement test. Next, rats underwent extinction training and a cue-induced reinstatement test. To assess how these variables contribute to heroin addiction vulnerability, we developed a network-based data analysis workflow. Specifically, we integrated different cohorts of rats, remove possible batch effects, and constructed a rat-rat similarity network based on their behavioral patterns. We then implemented community detection on this similarity network using a Bayesian degree-corrected stochastic block model to uncover sub-populations of rats with differing levels of opioid vulnerability. We discovered three distinct behavioral sub-populations, each with significantly different behavioral outcomes that allowed for unique characterization of each cluster in terms of vulnerability to opioid use and seeking. We implement this analysis workflow as an open source R package, named mlsbm.

animal behavior and cognition↗