According to the 2023 National Survey on Drug Use and Health (NSDUH), 28.9 million people ages 12 and older in the United States had alcohol use disorder (AUD) in the past year. Although chronic alcohol use contributes to numerous health disorders as well as being an economic burden, there are few medications approved for treatment of AUD, and these medications are not uniformly effective and are not widely used. We now describe studies of a small molecule, novel chemical entity called Nezavist, which shows promise as a medication to treat AUD and possibly other addictive disorders. Nezavist acts as a positive allosteric modulator at a novel site on the GABAA receptor, but pharmacokinetic analysis demonstrates that Nezavist does not enter the CNS. However, Nezavist effectively reduces relapse to chronic alcohol consumption in alcohol-dependent animals in two widely used models. An important goal of the current studies is to provide evidence for the hypothesis that Nezavist acts in the intestine to stimulate vagus nerve afferents that project to the brainstem (nucleus tractus solitarius), leading to reduced inflammation in the brain that may alleviate alcohol 'craving' during abstinence from alcohol. It is hoped that the presentation of the current results will stimulate interest in further confirmation of the mechanism of action of Nezavist, with the intent of developing a new and effective medication for treatment for AUD.
Background:At the invitation of the Journal, we are providing a summary of our published work that has followed the publication in 2009 of our manuscript entitled "Genetical Genomic Determinants of Alcohol Consumption in Rats and Humans". Our initial premise, which has been maintained throughout, is that knowledge regarding gene transcription would greatly enhance GWAS of alcohol-related phenotypes. We chose to concentrate our studies on the quantitative phenotype of alcohol consumption since high levels of alcohol consumption are a prerequisite for the development of alcohol use disorder (AUD). We also structured our studies to focus on "predisposition" to higher levels of alcohol consumption. We defined predisposition as a genetic structure and transcriptional pattern that is inherent in an organism and present prior to exposure to an environmental stimulus that engenders a physiological/behavioral response. In studies using humans, this interest in predisposition usually requires prolonged periods of cohort follow-up. On the other hand, studies with animals can use resources such as panels of recombinant inbred (RI) animals (in our case, the HXB/BXH rat panel) to capture the transcriptional landscape of animals not exposed to alcohol and compare this transcriptional landscape to levels of alcohol consumption collected from a different cohort of animals that are the same age, have an identical genetic composition, and are raised in an identical environment. The other benefit is that the stable genetic structure of inbred strains allows for a chronological expansion of information on these animals. This characteristic of the HXB/BXH RI rats allowed us to add important information as technology and analytical methods developed over time. Methods findings and conclusions:Our initial studies relied on hybridization arrays for RNA quantification in brain, an initial set of polymorphic markers for the rat genome, and a standard behavioral (b)QTL analysis for alcohol consumption. What we added to the conceptual basis for analysis and interpretation was the calculation of transcript expression (e)QTLs and the requirements that: 1. the eQTL overlapped the location of the bQTL; and 2. the transcript levels were significantly correlated with the quantitative levels of alcohol consumption across rat strains. These criteria were used to identify genes (transcripts) as "candidate" contributors to the alcohol consumption phenotype. We soon realized that the search for candidate genes as unique determinants of a complex trait is irrational, since these phenotypes are best characterized by differences in genetic networks. Therefore, we incorporated Weighted Gene Coexpression Network Analysis (WGCNA) in our further work. We also realized the limitations of hybridization arrays for breadth of transcriptome coverage and quantification, and in the more current work used total RNA-Seq-derived data for characterizing nearly all of the brain transcriptome. Finally, we participated in the efforts for whole genome sequencing of the strains of the HXB/BXH panel, generating an extensive new panel of markers for remapping of the QTLs. We also realized that the biological determinants of a behavioral phenotype do not have to reside in brain and, by examining the liver transcriptome, we found that the gut-liver-brain axis was, in part, involved in predisposition to higher levels of free-choice alcohol consumption. In all, from the first exploration of the genetical genomics of the alcohol consumption phenotype, to the current status of our work, the function of the brain immune system, with emphasis on microglia and astrocytes, even prior to the animal being offered alcohol, has emerged as a most significant genetic contributor to the amount of alcohol an animal will consume on a daily basis. Particularly prominent was a cluster of inflammasome (NLRP3)-modulating transcripts (P2rx4, Ift81, Oas1b, Txnip) and a long noncoding transcript, "Lrap" that repeatedly appeared within a gene coexpression module associated with alcohol consumption levels. Interestingly, data from post-mortem tissue from brain of humans suffering from AUD also indicates a hyperactive neuroimmune function. The data from studies with animals may indicate that neuroimmune hyperactivity may be a trait rather than a state marker for AUD.
The Hybrid Rat Diversity Panel (HRDP) is a stable and well-characterized set of more than 90 inbred rat strains that can be leveraged for systems genetics approaches to understanding the genetic and genomic variation associated with complex disease. The HRDP exhibits substantial between-strain diversity while retaining substantial within-strain isogenicity, allowing for the precise mapping of genetic variation associated with complex phenotypes and providing statistical power to identify associated variants. In order to robustly identify associated genetic variants, it is important to account for the population structure induced by inbreeding. To this end, we investigate the performance of four plausible approaches towards modeling quantitative traits in the HRDP and quantify their operating characteristics. In particular, we investigate three approaches based on genome-wide mixed model analysis, and one approach based on ordinary least squares linear regression. Towards facilitating study planning and design, we conduct extensive simulations to investigate the power of genetic association analyses in the HRDP, and characterize the impressive attained power. In simulation of eQTL data in the HRDP, we find that a mixed model approach that leverages leave-one-chromosome-out kinship estimation attains the highest power while controlling type I error.
Post transcriptional modifications of RNA are powerful mechanisms by which eukaryotes expand their genetic diversity. For instance, researchers estimate that most transcripts in humans undergo alternative splicing and alternative polyadenylation. These splicing events produce distinct RNA molecules, which in turn yield distinct protein isoforms and/or influence RNA stability, translation, nuclear export, and RNA/protein cellular localization. Due to their pervasiveness and impact, we hypothesized that alternative splicing and alternative polyadenylation in brain can contribute to a predisposition for voluntary alcohol consumption. Using the HXB/BXH recombinant inbred rat panel (a subset of the Hybrid Rat Diversity Panel), we generated over one terabyte of brain RNA sequencing data (total RNA) and identified novel splice variants (via StringTie) and alternative polyadenylation sites (via aptardi) to determine the transcriptional landscape in the brains of these animals. After establishing an analysis pipeline to ascertain high quality transcripts, we quantitated transcripts and integrated genotype data to identify candidate transcript coexpression networks and individual candidate transcripts associated with predisposition to voluntary alcohol consumption in the two-bottle choice paradigm. For genes that were previously associated with this trait (e.g., Lrap, Ift81, and P2rx4) (Saba et al., Febs. J., 282, 3556–3578, Saba et al., Genes. Brain. Behav., 20, e12698), we were able to distinguish between transcript variants to provide further information about the specific isoforms related to the trait. We also identified additional candidate transcripts associated with the trait of voluntary alcohol consumption (i.e., isoforms of Mapkapk5, Aldh1a7, and Map3k7). Consistent with our previous work, our results indicate that transcripts and networks related to inflammation and the immune system in brain can be linked to voluntary alcohol consumption. Overall, we have established a pipeline for including the quantitation of alternative splicing and alternative polyadenylation variants in the transcriptome in the analysis of the relationship between the transcriptome and complex traits.
The Hybrid Rat Diversity Panel (HRDP) is a stable and well-characterized set of more than 90 inbred rat strains that can be leveraged for systems genetics approaches to understanding the genetic and genomic variation associated with complex disease. The HRDP exhibits substantial between-strain diversity while retaining substantial within-strain isogenicity, allowing for the precise mapping of genetic variation associated with complex phenotypes and providing statistical power to identify associated variants. In order to robustly identify associated genetic variants, it is important to account for the population structure induced by inbreeding. To this end, we investigate the performance of various plausible approaches towards modeling quantitative traits in the HRDP and quantify their operating characteristics. Towards facilitating study planning and design, we conduct extensive simulations to investigate the power of genetic association analyses in the HRDP, and characterize the impressive attained power.
The translation of extracellular signals to intracellular responses involves a number of signal transduction molecules. A major component of this signal transducing function is adenylyl cyclase, which produces the intracellular "second messenger," cyclic AMP. What was initially considered as a single enzyme for cyclic AMP generation is now known to be a family of nine membrane-bound enzymes, and one cytosolic enzyme. Each member of the adenylyl cyclase family is distinguished by factors that modulate its catalytic activity, by the cell, tissue, and organ distribution of the family members, and by the physiological/behavioral functions that are subserved by particular family members. This review focuses on the Type 7 adenylyl cyclase (AC7) in terms of its catalytic characteristics and its relationship to alcohol use disorder (AUD, alcoholism), and major depressive disorder (MDD). AC7 may be part of the inherited system predisposing an individual to AUD and/or MDD in a sex-specific manner, or this enzyme may change in its expression or activity in response to the progression of disease or in response to treatment. The areas of brain expressing AC7 are related to responses to stress and evidence is available that CRF1 receptors are coupled to AC7 in the amygdala and pituitary. Interestingly, AC7 is the major form of the cyclase contained in bone marrow-derived cells of the immune system and platelets, and in microglia. AC7 is thus, poised to play an integral role in both peripheral and brain immune function thought to be etiologically involved in both AUD and MDD. Both platelet and lymphocyte adenylyl cyclase activity have been proposed as markers for AUD and MDD, as well as prognostic markers of positive response to medication for MDD. We finish with consideration of paths to medication development that may selectively modulate AC7 activity as treatments for MDD and AUD.
BACKGROUND:Alcohol use disorders (AUDs) are associated with altered regulation of physiological processes in the brain. Acetate, a metabolite of ethanol, has been implicated in several processes that are disrupted in AUDs including transcriptional regulation, metabolism, inflammation, and neurotransmission. To further understand the effects of acetate on brain function in AUDs, we investigated the effects of acetate on cerebral blood flow (CBF), systemic inflammatory cytokines, and behavior in AUD.METHODS:Sixteen participants with AUD were recruited from a nonmedical, clinically managed detoxification center. Each participant received acetate and placebo in a randomly assigned order of infusion and underwent 3T MR scanning using quantitative pseudo-continuous arterial spin labeling. Participants and the study team were blinded to the infusion. CBF values (ml/100 g/min) extracted from thalamus were compared between placebo and acetate using a mixed effect linear regression model accounting for infusion order. Voxel-wise CBF comparisons were set at threshold of p < 0.05 cluster-corrected for multiple comparisons, voxel-level p < 0.0001. Plasma cytokine levels and behavior were also assessed between infusions.RESULTS:Fifteen men and 1 woman were enrolled with Alcohol Use Disorders Identification Test (AUDIT) scores between 13 and 38 with a mean of 28.3 ± 9.1. Compared to placebo, acetate administration increased CBF in the thalamus bilaterally (Left: 51.2 vs. 68.8, p < 0.001; Right: 53.7 vs. 69.6, p = 0.001), as well as the cerebellum, brainstem, and cortex. Older age and higher AUDIT scores were associated with increases in acetate-induced thalamic blood flow. Cytokine levels and behavioral measures did not differ between placebo and acetate infusions.CONCLUSIONS:This pilot study in AUD suggests that during the first week of abstinence from alcohol, the brain's response to acetate differs by brain region and this response may be associated with the severity of alcohol dependence.
Background Cardiac hypertrophy can be considered a maladaptive response which in many cases results in heart failure and sudden death. Genetic predisposition to cardiac hypertrophy is ill-defined, but current research has given credence to a role of non-protein-coding RNAs in the development of cardiac hypertrophy. Results We used microarrays, RNA-Seq and quantitative genetics with the spontaneously hypertensive, SHR (SHR/OlaIpcv) rat strain, the normotensive Brown Norway (BN-Lx/Cub) rat strain, and a recombinant inbred (RI) panel of rats (HXB/BXH) derived from these strains to examine the areas of the genome associated with cardiac hypertrophy. We identified circular (circ) RNAs coded within these areas. Of the 122 differentially expressed circRNAs in left ventricle of SHR and BN-Lx rats, three were transcribed from areas corresponding to the QTLs we identified for cardiac hypertrophy using the HXB/BXH rat panel. We then identified microRNAs which are “sponged” by the circ RNAs and the mRNAs which are destabilized by the microRNAs. 265 miRNAs could be identified as targets for the three circRNAs. We focused on the four miRNAs that were also differentially expressed between SHR and BN-Lx rats. One of the miRNAs (Mir-210-5p) was a target of the differentially expressed circ H2afy and circ H2afy was located within the QTL on Chr 17 (genome wide p-value = 0.011). Mir-210-5p has a binding site on the 3’ UTR of DR6, which is differentially expressed and in turn controls the expression level of NFκB. NFκB is an important component of the oxidative stress response leading to hypertrophy. Conclusions Our work identified a novel circRNA that may be the mediator of a cascade of events that influence a cardiac hypertrophy phenotype. The circRNA and miRNA which we identified may become useful as markers of the risk for cardiac hypertrophy.
There is compelling evidence that sex and gender have crucial roles in excessive alcohol (ethanol) consumption. Here, we review some of the data from the perspective of brain transcriptional differences between males and females, focusing on rodent animal models. A key emerging transcriptional feature is the role of neuroimmune processes. Microglia are the resident neuroimmune cells in the brain and exhibit substantial functional differences between males and females. Selective breeding for binge ethanol consumption and the impacts of chronic ethanol consumption and withdrawal from chronic ethanol exposure all demonstrate sex-dependent neuroimmune signatures. A focus is on resolving sex-dependent differences in transcriptional responses to ethanol at the neurocircuitry level. Sex-dependent transcriptional differences are found in the extended amygdala and the nucleus accumbens. Telescoping of ethanol consumption is found in some, but not all, studies to be more prevalent in females. Recent transcriptional studies suggest that some sex differences may be due to female-dependent remodeling of the primary cilium. An interesting theme appears to be developing: at least from the animal model perspective, even when males and females are phenotypically similar, they differ significantly at the level of the transcriptome.
The following review article presents clinical and experimental features of alcohol-induced liver disease (ALD). Basic aspects of alcohol metabolism leading to the development of liver hepatotoxicity are discussed. ALD includes fatty liver, acute alcoholic hepatitis with or without liver failure, alcoholic steatohepatitis (ASH) leading to fibrosis and cirrhosis, and hepatocellular cancer (HCC). ALD is fully attributable to alcohol consumption. However, only 10–20% of heavy drinkers (persons consuming more than 40 g of ethanol/day) develop clinical ALD. Moreover, there is a link between behaviour and environmental factors that determine the amount of alcohol misuse and their liver disease. The range of clinical presentation varies from reversible alcoholic hepatic steatosis to cirrhosis, hepatic failure, and hepatocellular carcinoma. We aimed to (1) describe the clinico-pathology of ALD, (2) examine the role of immune responses in the development of alcoholic hepatitis (ASH), (3) propose diagnostic markers of ASH, (4) analyze the experimental models of ALD, (5) study the role of alcohol in changing the microbiota, and (6) articulate how findings in the liver and/or intestine influence the brain (and/or vice versa) on ASH; (7) identify pathways in alcohol-induced organ damage and (8) to target new innovative experimental concepts modeling the experimental approaches. The present review includes evidence recognizing the key toxic role of alcohol in ALD severity. Cytochrome p450 CYP2E1 activation may change the severity of ASH. The microbiota is a key element in immune responses, being an inducer of proinflammatory T helper 17 cells and regulatory T cells in the intestine. Alcohol consumption changes the intestinal microbiota and influences liver steatosis and liver inflammation. Knowing how to exploit the microbiome to modulate the immune system might lead to a new form of personalized medicine in ALF and ASH.
LncRNAs are important regulators of quantitative and qualitative features of the transcriptome. We have used QTL and other statistical analyses to identify a gene coexpression module associated with alcohol consumption. The "hub gene" of this module, Lrap (Long non-coding RNA for alcohol preference), was an unannotated transcript resembling a lncRNA. We used partial correlation analyses to establish that Lrap is a major contributor to the integrity of the coexpression module. Using CRISPR/Cas9 technology, we disrupted an exon of Lrap in Wistar rats. Measures of alcohol consumption in wild type, heterozygous and knockout rats showed that disruption of Lrap produced increases in alcohol consumption/alcohol preference. The disruption of Lrap also produced changes in expression of over 700 other transcripts. Furthermore, it became apparent that Lrap may have a function in alternative splicing of the affected transcripts. The GO category of "Response to Ethanol" emerged as one of the top candidates in an enrichment analysis of the differentially expressed transcripts. We validate the role of Lrap as a mediator of alcohol consumption by rats, and also implicate Lrap as a modifier of the expression and splicing of a large number of brain transcripts. A defined subset of these transcripts significantly impacts alcohol consumption by rats (and possibly humans). Our work shows the pleiotropic nature of non-coding elements of the genome, the power of network analysis in identifying the critical elements influencing phenotypes, and the fact that not all changes produced by genetic editing are critical for the concomitant changes in phenotype.
One of the most fruitful resources for systems genetic studies of nonhuman mammals is a panel of inbred strains that exhibits significant genetic diversity between strains but genetic stability (isogenicity) within strains. These characteristics allow for fine mapping of complex phenotypes (QTLs) and provide statistical power to identify loci which contribute nominally to the phenotype. This type of resource also allows the planning and performance of investigations using the same genetic backgrounds over several generations of the test animals. Often, rats are preferred over mice for physiologic and behavioral studies because of their larger size and more distinguishable anatomy (particularly for their central nervous system). The Hybrid Rat Diversity Panel (HRDP) is a panel of inbred rat strains, which combines two recombinant inbred panels (the HXB/BXH, 30 strains; the LEXF/FXLE, 34 strains and 35 more strains of inbred rats which were selected for genetic diversity, based on their fully sequenced genomes and/or thorough genotyping). The genetic diversity and statistical power of this panel for mapping studies rivals or surpasses currently available panels in mouse. The genetic stability of this panel makes it particularly suitable for collection of high-throughput omics data as relevant technology becomes available for engaging in truly integrative systems biology. The PhenoGen website (http://phenogen.org) is the repository for the initial transcriptome data, making the raw data, the processed data, and the analysis results, e.g., organ-specific protein coding and noncoding transcripts, isoform analysis, expression quantitative trait loci, and co-expression networks, available to the research public. The data sets and tools being developed will complement current efforts to analyze the human transcriptome and its genetic controls (the Genotype-Tissue Expression Project (GTEx)) and allow for dissection of genetic networks that predispose to particular phenotypes and gene-by-environment interactions that are difficult or even impossible to study in humans. The HRDP is an essential population for exploring truly integrative systems genetics.
BACKGROUND:MicroRNAs (miRNAs) are small non-coding RNAs that bind messenger RNAs and promote their degradation or repress their translation. There is increasing evidence of miRNAs playing an important role in alcohol related disorders. However, the role of miRNAs as mediators of the genetic effect on alcohol phenotypes is not fully understood. We conducted a high-throughput sequencing study to measure miRNA expression levels in alcohol naïve animals in the LXS panel of recombinant inbred (RI) mouse strains. We then combined the sequencing data with genotype data, microarry gene expression data, and data on alcohol-related behavioral phenotypes such as 'Drinking in the dark', 'Sleep time', and 'Low dose activation' from the same RI panel. SNP-miRNA-gene triplets with strong association within the triplet that were also associated with one of the 4 alcohol phenotypes were selected and a Bayesian network analysis was used to aggregate results into a directed network model.RESULTS:We found several triplets with strong association within the triplet that were also associated with one of the alcohol phenotypes. The Bayesian network analysis found two networks where a miRNA mediates the genetic effect on the alcohol phenotype. The miRNAs were found to influence the expression of protein-coding genes, which in turn influences the quantitative phenotypes. The pathways in which these genes are enriched have been previously associated with alcohol-related traits.CONCLUSION:This work enhances association studies by identifying miRNAs that may be mediating the association between genetic markers (SNPs) and the alcohol phenotypes. It suggests a mechanism of how genetic variants are affecting traits of interest through the modification of miRNA expression.
BACKGROUND:A statistical pipeline was developed and used for determining candidate genes and candidate gene coexpression networks involved in 2 alcohol (i.e., ethanol [EtOH]) metabolism phenotypes, namely alcohol clearance and acetate area under the curve in a recombinant inbred (RI) (HXB/BXH) rat panel. The approach was also used to provide an indication of how EtOH metabolism can impact the normal function of the identified networks.METHODS:RNA was extracted from alcohol-naïve liver tissue of 30 strains of HXB/BXH RI rats. The reconstructed transcripts were quantitated, and data were used to construct gene coexpression modules and networks. A separate group of rats, comprising the same 30 strains, were injected with EtOH (2 g/kg) for measurement of blood EtOH and acetate levels. These data were used for quantitative trait loci (QTL) analysis of the rate of EtOH disappearance and circulating acetate levels. The analysis pipeline required calculation of the module eigengene values, the correction of these values with EtOH metabolism rates and acetate levels across the rat strains, and the determination of the eigengene QTLs. For a module to be considered a candidate for determining phenotype, the module eigengene values had to have significant correlation with the strain phenotypic values and the module eigengene QTLs had to overlap the phenotypic QTLs.RESULTS:Of the 658 transcript coexpression modules generated from liver RNA sequencing data, a single module satisfied all criteria for being a candidate for determining the alcohol clearance trait. This module contained 2 alcohol dehydrogenase genes, including the gene whose product was previously shown to be responsible for the majority of alcohol elimination in the rat. This module was also the only module identified as a candidate for influencing circulating acetate levels. This module was also linked to the process of generation and utilization of retinoic acid as related to the autonomous immune response.CONCLUSIONS:We propose that our analytical pipeline can successfully identify genetic regions and transcripts which predispose a particular phenotype and our analysis provides functional context for coexpression module components.
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Aminoquinoline derivatives were evaluated against a panel of receptors/channels/transporters in radioligand binding experiments. One of these derivatives (DCUK-OEt) displayed micromolar affinity for brain γ-aminobutyric acid type A (GABAA) receptors. DCUK-OEt was shown to be a positive allosteric modulator (PAM) of GABA currents with α1β2γ2, α1β3γ2, α5β3γ2 and α1β3δ GABAA receptors, while having no significant PAM effect on αβ receptors or α1β1γ2, α1β2γ1, α4β3γ2 or α4β3δ receptors. DCUK-OEt modulation of α1β2γ2 GABAA receptors was not blocked by flumazenil. The subunit requirements for DCUK-OEt actions distinguished DCUK-OEt from other currently known modulators of GABA function (e.g., anesthetics, neurosteroids or ethanol). Simulated docking of DCUK-OEt at the GABAA receptor suggested that its binding site may be at the α + β- subunit interface. In slices of the central amygdala, DCUK-OEt acted primarily on extrasynaptic GABAA receptors containing the α1 subunit and generated increases in extrasynaptic "tonic" current with no significant effect on phasic responses to GABA. DCUK-OEt is a novel chemical structure acting as a PAM at particular GABAA receptors. Given that neurons in the central amygdala responding to DCUK-OEt were recently identified as relevant for alcohol dependence, DCUK-OEt should be further evaluated for the treatment of alcoholism.
Ethyl alcohol is a toxin that, when consumed at high levels, produces organ damage and death. One way to prevent or ameliorate this damage in humans is to reduce the exposure of organs to alcohol by reducing alcohol ingestion. Both the propensity to consume large volumes of alcohol and the susceptibility of human organs to alcohol-induced damage exhibit a strong genetic influence. We have developed an integrative genetic/genomic approach to identify transcriptional networks that predispose complex traits, including propensity for alcohol consumption and propensity for alcohol-induced organ damage. In our approach, the phenotype is assessed in a panel of recombinant inbred (RI) rat strains, and quantitative trait locus (QTL) analysis is performed. Transcriptome data from tissues/organs of naïve RI rat strains are used to identify transcriptional networks using Weighted Gene Coexpression Network Analysis (WGCNA). Correlation of the first principal component of transcriptional coexpression modules with the phenotype across the rat strains, and overlap of QTLs for the phenotype and the QTLs for the coexpression modules (module eigengene QTL) provide the criteria for identification of the functionally related groups of genes that contribute to the phenotype (candidate modules). While we previously identified a brain transcriptional module whose QTL overlapped with a QTL for levels of alcohol consumption in HXB/BXH RI rat strains and 12 selected rat lines, this module did not account for all of the genetic variation in alcohol consumption. Our search for QTL overlap and correlation of coexpression modules with phenotype can, however, be applied to any organ in which the transcriptome has been measured, and this represents a holistic approach in the search for genetic contributors to complex traits. Previous work has implicated liver/brain interactions, particularly involving inflammatory/immune processes, as influencing alcohol consumption levels. We have now analyzed the liver transcriptome of the HXB/BXH RI rat panel in relation to the behavioral trait of alcohol consumption. We used RNA-Seq and microarray data to construct liver transcriptional networks, and identified a liver candidate transcriptional coexpression module that explained 24% of the genetic variance in voluntary alcohol consumption. The transcripts in this module focus attention on liver secretory products that influence inflammatory and immune signaling pathways. We propose that these liver secretory products can interact with brain mechanisms that affect alcohol consumption, and targeting these pathways provides a potential approach to reducing high levels of alcohol intake and also protecting the integrity of the liver and other organs.
Although rat is a critical model organism in preclinical medications development, its use in systems genetics studies remains sparse. The PhenoGen database and website contain detailed information on the qualitative and quantitative aspects of the rat brain, liver, heart, and brown adipose transcriptome. This database has been generated using the HXB/BXH recombinant inbred panel and is being expanded to a hybrid rat diversity panel that includes many common inbred strains as well. By using such a panel, the PhenoGen project has created a renewable and cumulative resource for the rat genomics community. The database has been used to reconstruct the brain transcriptome identifying both annotated and unannotated transcribed elements that range in size from 20 nucleotides to over 30,000 nucleotides and elements that have a wide variety of roles in the cell including generation of proteins and regulation of the transcription and translation processes. In all 4 tissues, baseline transcriptional connectomes have been generated to model the relationships among transcripts. These connectomes can be used to identify genetic pathways associated with complex traits and to gain insight into biological function of individual transcripts. The PhenoGen website contains tools that allow the user to explore qualitative features of individual genes and to see how the gene relates to other genes within a tissue. The PhenoGen database and website continue to grow and to make use of the latest statistical methods for systems genetics creating a national resource for the rat genomics community.
Recent understanding of the systems that mediate complex disease states, has generated a search for molecules that simultaneously modulate more than one component of a pathologic pathway. Chronic pain syndromes are etiologically connected to functional changes (sensitization) in both peripheral sensory neurons and in the central nervous system (CNS). These functional changes involve modifications of a significant number of components of signal generating, signal transducing and signal propagating pathways. Our analysis of disease-related changes which take place in sensory neurons during sensitization led to the design of a molecule that would simultaneously inhibit peripheral NMDA receptors and voltage sensitive sodium channels. In the current report, we detail the selectivity of N,N-(diphenyl)-4-ureido-5,7-dichloro-2-carboxy-quinoline (DCUKA) for action at NMDA receptors composed of different subunit combinations and voltage sensitive sodium channels having different α subunits. We show that DCUKA is restricted to the periphery after oral administration, and that circulating blood levels are compatible with its necessary concentrations for effects at the peripheral cognate receptors/channels that were assayed in vitro. Our results demonstrate that DCUKA, at concentrations circulating in the blood after oral administration, can modulate systems which are upregulated during peripheral sensitization, and are important for generating and conducting pain information to the CNS. Furthermore, we demonstrate that DCUKA ameliorates the hyperalgesia of chronic pain without affecting normal pain responses in neuropathic and inflammation-induced chronic pain models.
Gene co-expression analysis has proven to be a powerful tool for ascertaining the organization of gene products into networks that are important for organ function. An organ, such as the liver, engages in a multitude of functions important for the survival of humans, rats, and other animals; these liver functions include energy metabolism, metabolism of xenobiotics, immune system function, and hormonal homeostasis. With the availability of organ-specific transcriptomes, we can now examine the role of RNA transcripts (both protein-coding and non-coding) in these functions. A systems genetic approach for identifying and characterizing liver gene networks within a recombinant inbred panel of rats was used to identify genetically regulated transcriptional networks (modules). For these modules, biological consensus was found between functional enrichment analysis and publicly available phenotypic quantitative trait loci (QTL). In particular, the biological function of two liver modules could be linked to immune response. The eigengene QTLs for these co-expression modules were located at genomic regions coincident with highly significant phenotypic QTLs; these phenotypes were related to rheumatoid arthritis, food preference, and basal corticosterone levels in rats. Our analysis illustrates that genetically and biologically driven RNA-based networks, such as the ones identified as part of this research, provide insight into the genetic influences on organ functions. These networks can pinpoint phenotypes that manifest through the interaction of many organs/tissues and can identify unannotated or under-annotated RNA transcripts that play a role in these phenotypes.