Genomic Loci Influencing Cue-Reactivity in Heterogeneous Stock Rats.

Addiction vulnerability is associated with the tendency to attribute incentive salience to reward predictive cues; both addiction and the attribution of incentive salience are influenced by environmental and genetic factors. To characterize the genetic contributions to incentive salience attribution, we performed a genome-wide association study (GWAS) in a cohort of 1,645 genetically diverse heterogeneous stock (HS) rats. We tested HS rats in a Pavlovian conditioned approach task, in which we characterized the individual responses to food-associated stimuli ("cues"). Rats exhibited either cue-directed "sign-tracking" behavior or food-cup directed "goal-tracking" behavior. We then used the conditioned reinforcement procedure to determine whether rats would perform a novel operant response for unrewarded presentations of the cue. We found that these measures were moderately heritable (SNP heritability, h2 = .189-.215). GWAS identified 14 quantitative trait loci (QTLs) for 11 of the 12 traits we examined. Interval sizes of these QTLs varied widely. 7 traits shared a QTL on chromosome 1 that contained a few genes (e.g. Tenm4, Mir708) that have been associated with substance use disorders and other mental health traits in humans. Other candidate genes (e.g. Wnt11, Pak1) in this region had coding variants and expression-QTLs in mesocorticolimbic regions of the brain. We also conducted a Phenome-Wide Association Study (PheWAS) on other behavioral measures in HS rats and found that regions containing QTLs on chromosome 1 were also associated with nicotine self-administration in a separate cohort of HS rats. These results provide a starting point for the molecular genetic dissection of incentive salience and provide further support for a relationship between attribution of incentive salience and drug abuse-related traits.

Environmental enrichment promotes adaptive responding during tests of behavioral regulation in male heterogeneous stock rats.

Organisms must regulate their behavior flexibly in the face of environmental challenges. Failure can lead to a host of maladaptive behavioral traits associated with a range of neuropsychiatric disorders, including attention deficit hyperactivity disorder, autism, and substance use disorders. This maladaptive dysregulation of behavior is influenced by genetic and environmental factors. For example, environmental enrichment produces beneficial neurobehavioral effects in animal models of such disorders. The present study determined the effects of environmental enrichment on a range of measures related to behavioral regulation using a large cohort of male, outbred heterogeneous stock (HS) rats as subjects. Subjects were reared from late adolescence onwards either in pairs in standard housing with minimal enrichment (n = 200) or in groups of 16 in a highly enriched environment consisting of a large multi-level cage filled with toys, running wheels, and shelters (n = 64). Rats were subjected to a battery of tests, including: (i) locomotor response to novelty, (ii) light reinforcement, (iii) social reinforcement, (iv) reaction time, (v) a patch-depletion foraging test, (vi) Pavlovian conditioned approach, (vii) conditioned reinforcement, and (viii) cocaine conditioned cue preference. Results indicated that rats housed in the enriched environment were able to filter out irrelevant stimuli more effectively and thereby regulate their behavior more efficiently than standard-housing rats. The dramatic impact of environmental enrichment suggests that behavioral studies using standard housing conditions may not generalize to more complex environments that may be more ethologically relevant.

Genome-wide association studies of human and rat BMI converge on synapse, epigenome, and hormone signaling networks.

A vexing observation in genome-wide association studies (GWASs) is that parallel analyses in different species may not identify orthologous genes. Here, we demonstrate that cross-species translation of GWASs can be greatly improved by an analysis of co-localization within molecular networks. Using body mass index (BMI) as an example, we show that the genes associated with BMI in humans lack significant agreement with those identified in rats. However, the networks interconnecting these genes show substantial overlap, highlighting common mechanisms including synaptic signaling, epigenetic modification, and hormonal regulation. Genetic perturbations within these networks cause abnormal BMI phenotypes in mice, too, supporting their broad conservation across mammals. Other mechanisms appear species specific, including carbohydrate biosynthesis (humans) and glycerolipid metabolism (rodents). Finally, network co-localization also identifies cross-species convergence for height/body length. This study advances a general paradigm for determining whether and how phenotypes measured in model species recapitulate human biology.

Environmental enrichment promotes adaptive responding during tests of behavioral regulation in male heterogeneous stock rats.

Organisms must regulate their behavior flexibly in the face of environmental challenges. Failure can lead to a host of maladaptive behavioral traits associated with a range of neuropsychiatric disorders, including attention deficit hyperactivity disorder, autism, and substance use disorders. This maladaptive dysregulation of behavior is influenced by genetic and environmental factors. For example, environmental enrichment produces beneficial neurobehavioral effects in animal models of such disorders. The present study determined the effects of environmental enrichment on a range of measures related to behavioral regulation using a large cohort of male, outbred heterogeneous stock (HS) rats as subjects to mimic the genetic variability found in the human population. Subjects were reared from late adolescence onwards either in pairs in standard housing with minimal enrichment (n=200) or in groups of 16 in a highly enriched environment consisting of a large multi-level cage filled with toys, running wheels, and shelters (n=64). Rats were subjected to a battery of tests, including: (i) locomotor response to novelty, (iI) light reinforcement, (iii) social reinforcement, (iv) reaction time, (v) a patch-depletion foraging test, (vi) Pavlovian conditioned approach, (vii) conditioned reinforcement, and (viii) cocaine conditioned cue preference. Results indicated that rats housed in the enriched environment were able to filter out irrelevant stimuli more effectively and thereby regulate their behavior more efficiently than standard-housing rats. The dramatic impact of environmental enrichment suggests that behavioral studies using standard housing conditions may not generalize to more complex environments that may be more ethologically relevant.

Automated quantitative trait locus analysis (AutoQTL).

BACKGROUND: Quantitative Trait Locus (QTL) analysis and Genome-Wide Association Studies (GWAS) have the power to identify variants that capture significant levels of phenotypic variance in complex traits. However, effort and time are required to select the best methods and optimize parameters and pre-processing steps. Although machine learning approaches have been shown to greatly assist in optimization and data processing, applying them to QTL analysis and GWAS is challenging due to the complexity of large, heterogenous datasets. Here, we describe proof-of-concept for an automated machine learning approach, AutoQTL, with the ability to automate many complicated decisions related to analysis of complex traits and generate solutions to describe relationships that exist in genetic data. RESULTS: Using a publicly available dataset of 18 putative QTL from a large-scale GWAS of body mass index in the laboratory rat, Rattus norvegicus, AutoQTL captures the phenotypic variance explained under a standard additive model. AutoQTL also detects evidence of non-additive effects including deviations from additivity and 2-way epistatic interactions in simulated data via multiple optimal solutions. Additionally, feature importance metrics provide different insights into the inheritance models and predictive power of multiple GWAS-derived putative QTL. CONCLUSIONS: This proof-of-concept illustrates that automated machine learning techniques can complement standard approaches and have the potential to detect both additive and non-additive effects via various optimal solutions and feature importance metrics. In the future, we aim to expand AutoQTL to accommodate omics-level datasets with intelligent feature selection and feature engineering strategies.

An exponential increase in QTL detection with an increased sample size.

Power analyses are often used to determine the number of animals required for a genome-wide association study (GWAS). These analyses are typically intended to estimate the sample size needed for at least 1 locus to exceed a genome-wide significance threshold. A related question that is less commonly considered is the number of significant loci that will be discovered with a given sample size. We used simulations based on a real data set that consisted of 3,173 male and female adult N/NIH heterogeneous stock rats to explore the relationship between sample size and the number of significant loci discovered. Our simulations examined the number of loci identified in subsamples of the full data set. The subsampling analysis was conducted for 4 traits with low (0.15 ± 0.03), medium (0.31 ± 0.03 and 0.36 ± 0.03), and high (0.46 ± 0.03) SNP-based heritabilities. For each trait, we subsampled the data 100 times at different sample sizes (500, 1,000, 1,500, 2,000, and 2,500). We observed an exponential increase in the number of significant loci with larger sample sizes. Our results are consistent with similar observations in human GWAS and imply that future rodent GWAS should use sample sizes that are significantly larger than those needed to obtain a single significant result.

Automated quantitative trait locus analysis (AutoQTL).

Background: Quantitative Trait Locus (QTL) analysis and Genome-Wide Association Studies (GWAS) have the power to identify variants that capture significant levels of phenotypic variance in complex traits. However, effort and time are required to select the best methods and optimize parameters and pre-processing steps. Although machine learning approaches have been shown to greatly assist in optimization and data processing, applying them to QTL analysis and GWAS is challenging due to the complexity of large, heterogenous datasets. Here, we describe proof-of-concept for an automated machine learning approach, AutoQTL, with the ability to automate many complex decisions related to analysis of complex traits and generate diverse solutions to describe relationships that exist in genetic data. Results: Using a dataset of 18 putative QTL from a large-scale GWAS of body mass index in the laboratory rat, Rattus norvegicus , AutoQTL captures the phenotypic variance explained under a standard additive model while also providing evidence of non-additive effects including deviations from additivity and 2-way epistatic interactions from simulated data via multiple optimal solutions. Additionally, feature importance metrics provide different insights into the inheritance models and predictive power of multiple GWAS-derived putative QTL. Conclusions: This proof-of-concept illustrates that automated machine learning techniques can be applied to genetic data and has the potential to detect both additive and non-additive effects via various optimal solutions and feature importance metrics. In the future, we aim to expand AutoQTL to accommodate omics-level datasets with intelligent feature selection strategies.

The incentive amplifying effects of nicotine: Roles in alcohol seeking and consumption.

Nicotine has a unique profile among drugs of abuse. To the noninitiated user, nicotine has powerful aversive effects and its relatively weak euphorigenic effects undergo rapid tolerance. Despite this, nicotine is commonly abused despite negative heath consequences, and nicotine users have enormous difficulty quitting. Further, nicotine is one of the most commonly co-abused substances, in that it is often taken in combination with other drugs. One explanation of this polydrug use is that nicotine has multiple appetitive and consummatory conditioning effects. For example, nicotine is a reinforcement enhancer in that it can potently increase the incentive value of other stimuli, including those surrounding drugs of abuse such as alcohol. In addition, nicotine also has a unique profile of neurobiological effects that alter regulation of alcohol intake and interoception. This review discusses the psychological and biological mechanisms surrounding nicotine's appetitive conditioning and consummatory effects, particularly its interactions with alcohol.

Systemic nicotine enhances opioid self-administration and modulates the formation of opioid-associated memories partly through actions within the insular cortex.

Habitual use of nicotine containing products increases propensity to misuse prescription opioids and its prevalence is substantially increased in individuals currently involved in opioid-treatment programs. Nicotine enhances self-administration of many classes of drugs in rodents, though evidence for direct effects on opioids is lacking. We sought to measure the effects of nicotine pretreatment on the reinforcing efficacy of opioids in both self-administration and contextual conditioning paradigms. First, we measured the effect of systemic nicotine pretreatment on self-administration of two opioids. Additionally, we measured the degree to which systemic nicotine pretreatment impacts the formation of morphine-associated contextual memories in conditioned taste avoidance and place preference paradigms. Given the involvement of the insula in the maintenance of substance abuse, its importance in nicotine addiction, and findings that insular inactivation impairs contextual drug conditioning, we examined whether nicotine administered directly to the insula could recapitulate the effects of systemic nicotine. We demonstrate that systemic nicotine pretreatment significantly enhances opioid self-administration and alters contextual conditioning. Furthermore, intra-insula nicotine similarly altered morphine contextual conditioning by blocking the formation of taste avoidance at all three morphine doses tested (5.0, 10, and 20 mg/kg), while shifting the dose-response curve of morphine in the place preference paradigm rightward. In conclusion, these data demonstrate that nicotine facilitates opioid intake and is partly acting within the insular cortex to obfuscate aversive opiate memories while potentiating approach to morphine-associated stimuli at higher doses.

Sensitivity to food and cocaine cues are independent traits in a large sample of heterogeneous stock rats.

Sensitivity to cocaine and its associated stimuli ("cues") are important factors in the development and maintenance of addiction. Rodent studies suggest that this sensitivity is related, in part, to the propensity to attribute incentive salience to food cues, which, in turn, contributes to the maintenance of cocaine self-administration, and cue-induced relapse of drug-seeking. Whereas each of these traits has established links to drug use, the relatedness between the individual traits themselves has not been well characterized in preclinical models. To this end, the propensity to attribute incentive salience to a food cue was first assessed in two distinct cohorts of 2716 outbred heterogeneous stock rats (HS; formerly N:NIH). We then determined whether each cohort was associated with performance in one of two paradigms (cocaine conditioned cue preference and cocaine contextual conditioning). These measure the unconditioned locomotor effects of cocaine, as well as conditioned approach and the locomotor response to a cocaine-paired floor or context. There was large individual variability and sex differences among all traits, but they were largely independent of one another in both males and females. These findings suggest that these traits may contribute to drug-use via independent underlying neuropsychological processes.

Genome-Wide Association Study in 3,173 Outbred Rats Identifies Multiple Loci for Body Weight, Adiposity, and Fasting Glucose.

OBJECTIVE: Obesity is influenced by genetic and environmental factors. Despite the success of human genome-wide association studies, the specific genes that confer obesity remain largely unknown. The objective of this study was to use outbred rats to identify the genetic loci underlying obesity and related morphometric and metabolic traits. METHODS: This study measured obesity-relevant traits, including body weight, body length, BMI, fasting glucose, and retroperitoneal, epididymal, and parametrial fat pad weight in 3,173 male and female adult N/NIH heterogeneous stock (HS) rats across three institutions, providing data for the largest rat genome-wide association study to date. Genetic loci were identified using a linear mixed model to account for the complex family relationships of the HS and using covariates to account for differences among the three phenotyping centers. RESULTS: This study identified 32 independent loci, several of which contained only a single gene (e.g., Epha5, Nrg1, Klhl14) or obvious candidate genes (e.g., Adcy3, Prlhr). There were strong phenotypic and genetic correlations among obesity-related traits, and there was extensive pleiotropy at individual loci. CONCLUSIONS: This study demonstrates the utility of HS rats for investigating the genetics of obesity-related traits across institutions and identify several candidate genes for future functional testing.

Sex-dependent associations between addiction-related behaviors and the microbiome in outbred rats.

BACKGROUND: Multiple factors contribute to the etiology of addiction, including genetics, sex, and a number of addiction-related behavioral traits. One behavioral trait where individuals assign incentive salience to food stimuli ("sign-trackers", ST) are more impulsive compared to those that do not ("goal-trackers", GT), as well as more sensitive to drugs and drug stimuli. Furthermore, this GT/ST phenotype predicts differences in other behavioral measures. Recent studies have implicated the gut microbiota as a key regulator of brain and behavior, and have shown that many microbiota-associated changes occur in a sex-dependent manner. However, few studies have examined how the microbiome might influence addiction-related behaviors. To this end, we sought to determine if gut microbiome composition was correlated with addiction-related behaviors determined by the GT/ST phenotype. METHODS: Outbred male (N=101) and female (N=101) heterogeneous stock rats underwent a series of behavioral tests measuring impulsivity, attention, reward-learning, incentive salience, and locomotor response. Cecal microbiome composition was estimated using 16S rRNA gene amplicon sequencing. Behavior and microbiome were characterized and correlated with behavioral phenotypes. Robust sex differences were observed in both behavior and microbiome; further analyses were conducted within sex using the pre-established goal/sign-tracking (GT/ST) phenotype and partial least squares differential analysis (PLS-DA) clustered behavioral phenotype. RESULTS: Overall microbiome composition was not associated to the GT/ST phenotype. However, microbial alpha diversity was significantly decreased in female STs. On the other hand, a measure of impulsivity had many significant correlations to microbiome in both males and females. Several measures of impulsivity were correlated with the genus Barnesiella in females. Female STs had notable correlations between microbiome and attentional deficient. In both males and females, many measures were correlated with the bacterial families Ruminocococcaceae and Lachnospiraceae. CONCLUSIONS: These data demonstrate correlations between several addiction-related behaviors and the microbiome specific to sex.

The tendency to sign-track predicts cue-induced reinstatement during nicotine self-administration, and is enhanced by nicotine but not ethanol.

RATIONALE: Some individuals are particularly responsive to reward-associated stimuli ("cues"), including the effects of these cues on craving and relapse to drug-seeking behavior. In the cases of nicotine and alcohol, cues may acquire these abilities via the incentive-enhancing properties of the drug. OBJECTIVES: To determine the interaction between cue-responsivity and nicotine reinforcement, we studied the patterns of nicotine self-administration in rats categorized based on their tendency to approach a food-predictive cue ("sign-trackers") or a reward-delivery location ("goal-trackers"). In a second experiment, we determined whether nicotine and ethanol altered the incentive value of a food cue. METHODS: Rats were classified as sign- or goal-trackers during a Pavlovian conditioned approach paradigm. Rats then self-administered intravenous nicotine (0.03 mg/kg infusions) followed by extinction and cue-induced reinstatement tests. We also tested the effects of nicotine (0.4 mg/kg base s.c.) or ethanol (0.7 g/kg i.p.) on the approach to, and reinforcing efficacy of, a food cue. RESULTS: Sign-trackers showed greater reinstatement in response to a nicotine cue. Further, nicotine enhanced sign-tracking but not goal-tracking to a food cue and also enhanced responding for the food cue during the conditioned reinforcement test. Conversely, ethanol reduced sign-tracking and increased goal-tracking, but had no effect on conditioned reinforcement. CONCLUSIONS: Our studies demonstrate that the tendency to attribute incentive value to a food cue predicts enhanced cue-induced reinstatement. Additionally, the incentive value of food cues is differentially modulated by nicotine and ethanol, which may be related to the reinforcing effects of these drugs.

Premature responding is associated with approach to a food cue in male and female heterogeneous stock rats.

RATIONALE: Disorders of behavioral regulation, including attention deficit hyperactivity disorder (ADHD) and drug addiction, are in part due to poor inhibitory control, attentional deficits, and hyper-responsivity to reward-associated cues. OBJECTIVES: To determine whether these traits are related, we tested genetically variable male and female heterogeneous stock rats in the choice reaction time (CRT) task and Pavlovian conditioned approach (PavCA). Sex differences in the response to methylphenidate during the CRT were also assessed. METHODS: In the CRT task, rats were required to withhold responding until one of two lights indicated whether responses into a left or right port would be reinforced with water. Reaction time on correct trials and premature responses were the operational definitions of attention and response inhibition, respectively. Rats were also pretreated with oral methylphenidate (0, 2, 4 mg/kg) during the CRT task to determine whether this drug would improve performance. Subsequently, during PavCA, presentation of an illuminated lever predicted the delivery of a food pellet into a food-cup. Lever-directed approach (sign-tracking) and food-cup approach (goal-tracking) were the primary measures, and rats were categorized as "sign-trackers" and "goal-trackers" using an index based on these measures. RESULTS: Sign-trackers made more premature responses than goal-trackers but showed no differences in reaction time. There were sex differences in both tasks, with females having higher sign-tracking, completing more CRT trials, and making more premature responses after methylphenidate administration. CONCLUSIONS: These results indicate that response inhibition is related to reward-cue responsivity, suggesting that these traits are influenced by common genetic factors.

Motivational Processes Underlying Substance Abuse Disorder.

Drug addiction is a syndrome of dysregulated motivation, evidenced by intense drug craving and compulsive drug-seeking behavior. In the search for 'common neurobiological substrates of addiction to different classes of drugs, behavioral neuroscientists have attempted to determine the neural basis for a number of motivational concepts and describe how they are changed by repeated drug use. Here, we describe these concepts and summarize previous work describing three major neural systems that play distinct roles in different conceptual aspects of motivation: (1) a nigrostriatal system that is involved in two forms of instrumental learning, (2) a ventral striatal system that is involved in Pavlovian incentive motivation and negative reinforcement, and (3) frontal cortical areas that regulate decision making and motivational processes. Within striatal systems, drug addiction can involve a transition from goal-oriented, incentive processes to automatic, habit-based responding. In the cortex, weak inhibitory control is a predisposing factor to, as well as a consequence of, repeated drug intake. However, these transitions are not absolute, and addiction can occur without a transition to habit-based responding, occurring as a result of the overvaluation of drug outcomes and hypersensitivity to incentive properties of drug-associated cues. Finally, we point out that addiction is not monolithic and can depend not only on individual differences between addicts, but also on the neurochernical action of specific drug classes.