Biology subjects

Ciccocioppo, R.

Publications and source records attributed to Ciccocioppo, R..

10 recordsLinked to original sources

bioRxiv2026

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↗

bioRxiv2026

Single-cell multi-omics maps clonal IEL expansion and epithelial remodelling in refractory coeliac disease

Background Refractory coeliac disease type 1 (RCD1) lacks defining molecular markers, and the immune and epithelial mechanisms sustaining intestinal injury remain poorly understood. Objective To define the clonal immune and epithelial states that distinguish RCD1 from active coeliac disease (ACD) and determine their spatial organisation in the duodenal mucosa. Design We integrated single-cell RNA sequencing, CITE-seq surface proteomics and paired T-cell receptor sequencing of duodenal immune and epithelial compartments from Healthy controls (n = 6), ACD (n = 7), RCD1 (n = 9) and RCD2 (n = 2), with spatial transcriptomics in a subset of biopsies. Results RCD1 showed widespread TCR{beta} and TCR{gamma}{delta} clonal expansion across multiple IEL states, extending beyond previously defined mutation-bearing aberrant clones. Distinct IEL populations converged on a shared programme of adaptive persistence, innate-like signalling, metabolic fitness and cytoskeletal remodelling; GZMK expression marked both clonally expanded and non-clonal disease-associated states. In parallel, RCD1 epithelium showed loss of mature absorptive cell states and expansion of stress-associated, immune-interacting and regenerative programmes. Transit-amplifying cells acquired differentiation and tissue-remodelling signatures, while enteroendocrine cells expanded and developed a sensory-neurosecretory programme involving TRPA1, TRPV1, vesicle trafficking and NEUROD1 regulon activity. Spatial transcriptomics localised regenerative and enteroendocrine-associated epithelial programmes adjacent to immune-visible epithelial regions and KLRK1/GZMK-expressing IEL-rich niches in refractory tissue. Conclusion RCD1 represents a distinct mucosal state characterised by coordinated clonal IEL adaptation and epithelial remodelling, rather than simple amplification of ACD, providing a cellular framework for persistent tissue injury and disease stratification.

immunology↗

bioRxiv2025

Machine Learning-Based Model for Behavioral Analysis in Rodents: Application to the Forced Swim Test

The Forced Swim Test (FST) is a widely used preclinical model for assessing antidepressant efficacy, studying stress response, and evaluating depressive-like behaviours in rodents. Over the last 10 years, more than 5,500 scientific articles reporting the use of the FST have been published. Despite its widespread use, the FST behaviours are still manually scored, resulting in a labor-intensive and time-consuming process that is prone to human bias and variability. Despite eliminating some biases, existing automated systems are costly and typically only able to distinguish between immobility and active behaviours. Therefore, they are often unable to accurately differentiate the major subtypes of movement patterns, such as swimming and climbing. To address these limitations, we propose a novel approach based on machine learning (ML) using a three-dimensional residual convolutional neural network (3D RCNN) that processes video pixels directly, capturing the spatiotemporal dynamics of rodent behaviour. Our ML model was validated against manual scoring in rats treated with fluoxetine and desipramine, two antidepressants known to induce distinct behavioural patterns. The ML model successfully differentiated among swimming, climbing, and immobility behaviours, demonstrating its potential as a standardized and unbiased tool for automatized behavioural analysis in the FST. Subsequently, we successfully validated our model by testing its ability to distinguish between drugs that predominantly evoke climbing (i.e., amitriptyline), those that preferentially facilitate swimming (i.e., paroxetine), and those that evoke both in a more balanced manner (i.e., venlafaxine). This approach represents a significant advancement in preclinical research, providing a more accurate and efficient method to analyze forced swimming data in rodents. We anticipate that due to its adaptability, in addition to the FST, the model could be applied to various behavioural tests in laboratory animals.

neuroscience↗

bioRxiv2024

Translating human drug use patterns into rat models: exploring spontaneous interindividual differences via refined drug self-administration procedures

Heroin and cocaine users tailor their dosage and frequency of use, as well as their method of administration, to maximize the drugs pleasurable effects and prevent withdrawal symptoms. On the other hand, many preclinical self-administration and choice experiments employ fixed unit doses and mandatory timeouts after doses (known as discrete dimension procedures). These restrictions fail to consider the distinct pharmacokinetic properties of heroin and cocaine, leading to uniform and comparable behaviors (including drug-taking patterns). This uniformity contrasts sharply with the significantly different ways humans use heroin and cocaine, which are characterized by highly individualized drug use behaviors. Here, we introduce a no-timeout procedure that overcomes this limitation (continuous dimension procedure). We analyzed the heroin and cocaine taking- and seeking-patterns and estimated drug-brain levels in the presence or absence of timeout between drug injections. We further assessed how absence of timeout and the availability of drug or social peer (access time to the two rewards) affect drug preference. Removing the timeout had a profound effect on pattern of heroin taking and seeking, promoting the emergence of burst-like drug intake and social withdrawal as revealed by a discrete choice procedure. On the other hand, timeout removal had a lesser impact on cocaine taking and seeking and did not impact social preference. By removing timeout during self-administration and increasing the access time during choice resulted in a self-administration procedure that more closely mimic human heroin intake, offering a platform to identify novel medications.

neuroscience↗

bioRxiv2024

Genome-wide association study reveals multiple loci for analgesia and heroin taking behavior in outbred rats

The increased prevalence of opioid use disorder (OUD) makes it imperative to disentangle the biological mechanisms contributing to individual differences in OUD vulnerability. OUD shows strong heritability, however genetic variants contributing to vulnerability remain poorly defined. We performed a genome-wide association study using over 850 male and female heterogeneous stock (HS) rats to identify genes underlying behaviors associated with OUD such as nociception, as well as heroin-taking, extinction and seeking behaviors. By using an animal model of OUD, we were able to identify genetic variants associated with distinct OUD behaviors while maintaining a uniform environment, an experimental design not easily achieved in humans. Furthermore, we used a novel non-linear network-based clustering approach to characterize rats based on OUD vulnerability to assess genetic variants associated with OUD susceptibility. Our findings confirm the heritability of several OUD-like behaviors, including OUD susceptibility. Additionally, several genetic variants associated with nociceptive threshold prior to heroin experience, heroin consumption, escalation of intake, and motivation to obtain heroin were identified. Tom1, a microglial component, was implicated for nociception. Several genes involved in dopaminergic signaling, neuroplasticity and substance use disorders, including Brwd1, Pcp4, Phb1l2 and Mmp15 were implicated for the heroin traits. Additionally, an OUD vulnerable phenotype was associated with genetic variants for consumption and break point, suggesting a specific genetic contribution for OUD-like traits contributing to vulnerability. Together, these findings identify novel genetic markers related to the susceptibility to OUD-relevant behaviors in HS rats.

genetics↗

bioRxiv2024

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↗

bioRxiv2024

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↗

bioRxiv2023

Adolescent chronic sleep restriction promotes alcohol drinking in adulthood: evidence from epidemiological and preclinical data.

Epidemiological investigations have indicated that insufficient sleep is prevalent among adolescents, posing a globally underestimated health risk. Sleep fragmentation and sleep loss during adolescence have been linked to concurrent emotional dysregulation and an increase in impulsive, risk-taking behaviors, including a higher likelihood of substance abuse. Among the most widely used substances, alcohol stands as the primary risk factor for deaths and disability among individuals aged 15-49 worldwide. While the association between sleep loss and alcohol consumption during adolescence is well documented, the extent to which prior exposure to sleep loss in adolescence contributes to heightened alcohol use later in adulthood remains less clearly delineated. Here, we analyzed longitudinal epidemiological data spanning 9 years, from adolescence to adulthood, including 5497 participants of the Avon Longitudinal Study of Parents And Children cohort. Sleep and alcohol measures collected from interviews and questionnaires at 15 and 24 years of age were analyzed with multivariable linear regression and a cross-lagged autoregressive path model. Additionally, we employed a controlled preclinical experimental setting to investigate the causal relationship underlying the associations found in the human study and to assess comorbid behavioral alterations. Preclinical data were collected by sleep restricting Marchigian Sardinian alcohol preferring rats (msP, n=40) during adolescence and measuring voluntary alcohol drinking concurrently and in adulthood. Polysomnography was used to validate the efficacy of the sleep restriction procedure. Behavioral tests were used to assess anxiety, risky behavior, and despair. In humans, after adjusting for covariates, we found a cross-sectional association between all sleep parameters and alcohol consumption at 15 years of age but not at 24 years. Notably, alcohol consumption (Alcohol Use Disorder Identification Test for Consumption) at 24 years was predicted by insufficient sleep at 15 years whilst alcohol drinking at 15 years could not predict sleep problems at 24. In msP rats, adolescent chronic sleep restriction escalated alcohol consumption and led to increased propensity for risk-taking behavior in adolescence and adulthood. Our findings demonstrate that adolescent insufficient sleep causally contributes to higher adult alcohol consumption, potentially by promoting risky behavior.

neuroscience↗

bioRxiv2023

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↗

bioRxiv2021

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↗