A systematic review and meta-analysis on the transcriptomic signatures in alcohol use disorder.

Currently available clinical treatments on alcohol use disorder (AUD) exhibit limited efficacy and new druggable targets are required. One promising approach to discover new molecular treatment targets involves the transcriptomic profiling of brain regions within the addiction neurocircuitry, utilizing animal models and postmortem brain tissue from deceased patients with AUD. Unfortunately, such studies suffer from large heterogeneity and small sample sizes. To address these limitations, we conducted a cross-species meta-analysis on transcriptome-wide data obtained from brain tissue of patients with AUD and animal models. We integrated 36 cross-species transcriptome-wide RNA-expression datasets with an alcohol-dependent phenotype vs. controls, following the PRISMA guidelines. In total, we meta-analyzed 964 samples - 502 samples from the prefrontal cortex (PFC), 282 nucleus accumbens (NAc) samples, and 180 from amygdala (AMY). The PFC had the highest number of differentially expressed genes (DEGs) across rodents, monkeys, and humans. Commonly dysregulated DEGs suggest conserved cross-species mechanisms for chronic alcohol consumption/AUD comprising MAPKs as well as STAT, IRF7, and TNF. Furthermore, we identified numerous unique gene sets that might contribute individually to these conserved mechanisms and also suggest novel molecular aspects of AUD. Validation of the transcriptomic alterations on the protein level revealed interesting targets for further investigation. Finally, we identified a combination of DEGs that are commonly regulated across different brain tissues as potential biomarkers for AUD. In summary, we provide a compendium of genes that are assessable via a shiny app, and describe signaling pathways, and physiological and cellular processes that are altered in AUD that require future studies for functional validation.

Effect of chronic ethanol consumption in rhesus macaques on the nucleus accumbens core transcriptome.

The nucleus accumbens core (NAcc) has been repeatedly demonstrated to be a key component of the circuitry associated with excessive ethanol consumption. Previous studies have illustrated that in a nonhuman primate (NHP) model of chronic ethanol consumption, there is significant epigenetic remodeling of the NAcc. In the current study, RNA-Seq was used to examine genome-wide gene expression in eight each of control, low/binge (LD*), and high/very high (HD*) rhesus macaque drinkers. Using an FDR < 0.05, zero genes were significantly differentially expressed (DE) between LD* and controls, six genes between HD* and LD*, and 734 genes between HD* and controls. Focusing on HD* versus control DE genes, the upregulated genes (N = 366) were enriched in genes with annotations associated with signal recognition particle (SRP)-dependent co-translational protein targeting to membrane (FDR < 3 × 10-59 ), structural constituent of ribosome (FDR < 3 × 10-47 ), and ribosomal subunit (FDR < 5 × 10-48 ). Downregulated genes (N = 363) were enriched in annotations associated with behavior (FDR < 2 × 10-4 ), membrane organization (FDR < 1 × 10-4 ), inorganic cation transmembrane transporter activity (FDR < 2 × 10-3 ), synapse part (FDR < 4 × 10-10 ), glutamatergic synapse (FDR < 1 × 10-6 ), and GABAergic synapse (FDR < 6 × 10-4 ). Ingenuity Pathway Analysis (IPA) revealed that EIF2 signaling and mTOR pathways were significantly upregulated in HD* animals (FDR < 3 × 10-33 and <2 × 10-16 , respectively). Overall, the data supported our working hypothesis; excessive consumption would be associated with transcriptional differences in GABA/glutamate-related genes.

Phenotypic and gene expression features associated with variation in chronic ethanol consumption in heterogeneous stock collaborative cross mice.

Of the more than 100 studies that have examined relationships between excessive ethanol consumption and the brain transcriptome, few rodent studies have examined chronic consumption. Heterogeneous stock collaborative cross mice freely consumed ethanol vs. water for 3 months. Transcriptional differences were examined for the central nucleus of the amygdala, a brain region known to impact ethanol preference. Early preference was modestly predictive of final preference and there was significant escalation of preference in females only. Genes significantly correlated with female preference were enriched in annotations for the primary cilium and extracellular matrix. A single module in the gene co-expression network was enriched in genes with an astrocyte annotation. The key hub node was the master regulator, orthodenticle homeobox 2 (Otx2). These data support an important role for the extracellular matrix, primary cilium and astrocytes in ethanol preference and consumption differences among individual female mice of a genetically diverse population.

RNA-Seq Analysis of Genetic and Transcriptome Network Effects of Dual-Trait Selection for Ethanol Preference and Withdrawal Using SOT and NOT Genetic Models.

BACKGROUND: Genetic factors significantly affect alcohol consumption and vulnerability to withdrawal. Furthermore, some genetic models showing predisposition to severe withdrawal are also predisposed to low ethanol (EtOH) consumption and vice versa, even when tested independently in naïve animals. METHODS: Beginning with a C57BL/6J × DBA/2J F2 intercross founder population, animals were simultaneously selectively bred for both high alcohol consumption and low acute withdrawal (SOT line), or vice versa (NOT line). Using randomly chosen fourth selected generation (S4) mice (N = 18-22/sex/line), RNA-Seq was employed to assess genome-wide gene expression in ventral striatum. The MegaMUGA array was used to detect genome-wide genotypic differences. Differential gene expression and the weighted gene co-expression network analysis were implemented as described elsewhere (Genes Brain Behav 16, 2017, 462). RESULTS: The new selection of the SOT and NOT lines was similar to that reported previously (Alcohol Clin Exp Res 38, 2014, 2915). One thousand eight hundred and sixteen transcripts were detected as differentially expressed between the lines. For genes more highly expressed in the SOT line, there was enrichment in genes associated with cell adhesion, synapse organization, and postsynaptic membrane. The genes with a cell adhesion annotation included 23 protocadherins, Mpdz and Dlg2. Genes with a postsynaptic membrane annotation included Gabrb3, Gphn, Grid1, Grin2b, Grin2c, and Grm3. The genes more highly expressed in the NOT line were enriched in a network module (red) with annotations associated with mitochondrial function. Several of these genes were module hub nodes, and these included Nedd8, Guk1, Elof1, Ndufa8, and Atp6v1f. CONCLUSIONS: Marked effects of selection on gene expression were detected. The NOT line was characterized by higher expression of hub nodes associated with mitochondrial function. Genes more highly expressed in the SOT aligned with previous findings, for example, Colville and colleagues (Genes Brain Behav 16, 2017, 462) that both high EtOH preference and consumption are associated with effects on cell adhesion and glutamate synaptic plasticity.

Chronic Voluntary Ethanol Drinking in Cynomolgus Macaques Elicits Gene Expression Changes in Prefrontal Cortical Area 46.

BACKGROUND: Genome-wide profiling to examine brain transcriptional features associated with excessive ethanol (EtOH) consumption has been applied to a variety of species including rodents, nonhuman primates (NHPs), and humans. However, these data were obtained from cross-sectional samples which are particularly vulnerable to individual variation when obtained from small outbred populations typical of human and NHP studies. In the current study, a novel within-subject design was used to examine the effects of voluntary EtOH consumption on prefrontal cortex (PFC) gene expression in a NHP model. METHODS: Two cohorts of cynomolgus macaques (n = 23) underwent a schedule-induced polydipsia procedure to establish EtOH self-administration followed by 6 months of daily open access to EtOH (4% w/v) and water. Individual daily EtOH intakes ranged from an average of 0.7 to 3.7 g/kg/d. Dorsal lateral PFC area 46 (A46) brain biopsies were collected in EtOH-naïve and control monkeys; contralateral A46 biopsies were collected from the same monkeys following the 6 months of fluid consumption. Gene expression changes were assessed using RNA-Seq paired analysis, which allowed for correction of individual baseline differences in gene expression. RESULTS: A total of 675 genes were significantly down-regulated following EtOH consumption; these were functionally enriched for immune response, cell adhesion, plasma membrane, and extracellular matrix. A total of 567 genes that were up-regulated following EtOH consumption were enriched in microRNA target sites and included target sites associated with Toll-like receptor pathways. The differentially expressed genes were also significantly enriched in transcription factor binding sites. CONCLUSIONS: The data presented here are the first to use a longitudinal biopsy strategy to examine how chronic EtOH consumption affects gene expression in the primate PFC. Prominent effects were seen in both cell adhesion and neuroimmune pathways; the latter contained both pro- and antiinflammatory genes. The data also indicate that changes in miRNAs and transcription factors may be important epigenetic regulators of EtOH consumption.

Gender-Specific Effects of Selection for Drinking in the Dark on the Network Roles of Coding and Noncoding RNAs.

BACKGROUND: Transcriptional differences between heterogeneous stock mice and high drinking-in-the-dark selected mouse lines have previously been described based on microarray technology coupled with network-based analysis. The network changes were reproducible in 2 independent selections and largely confined to 2 distinct network modules; in contrast, differential expression appeared more specific to each selected line. This study extends these results by utilizing RNA-Seq technology, allowing evaluation of the relationship between genetic risk and transcription of noncoding RNA (ncRNA); we additionally evaluate sex-specific transcriptional effects of selection. METHODS: Naïve mice (N = 24/group and sex) were utilized for gene expression analysis in the ventral striatum; the transcriptome was sequenced with the Illumina HiSeq platform. Differential gene expression and the weighted gene co-expression network analysis were implemented largely as described elsewhere, resulting in the identification of genes that change expression level or (co)variance structure. RESULTS: Across both sexes, we detect selection effects on the extracellular matrix and synaptic signaling, although the identity of individual genes varies. A majority of nc RNAs cluster in a single module of relatively low density in both the male and female network. The most strongly differentially expressed transcript in both sexes was Gm22513, a small nuclear RNA with unknown function. Associated with selection, we also found a number of network hubs that change edge strength and connectivity. At the individual gene level, there are many sex-specific effects; however, at the annotation level, results are more concordant. CONCLUSIONS: In addition to demonstrating sex-specific effects of selection on the transcriptome, the data point to the involvement of extracellular matrix genes as being associated with the binge drinking phenotype.

On the relationships in rhesus macaques between chronic ethanol consumption and the brain transcriptome.

This is the first description of the relationship between chronic ethanol self-administration and the brain transcriptome in a non-human primate (rhesus macaque). Thirty-one male animals self-administered ethanol on a daily basis for over 12 months. Gene transcription was quantified with RNA-Seq in the central nucleus of the amygdala (CeA) and cortical Area 32. We constructed coexpression and cosplicing networks, and we identified areas of preservation and areas of differentiation between regions and network types. Correlations between intake and transcription included largely distinct gene sets and annotation categories across brain regions and between expression and splicing; positive and negative correlations were also associated with distinct annotation groups. Membrane, synaptic and splicing annotation categories were over-represented in the modules (gene clusters) enriched in positive correlations (CeA); our cosplicing analysis further identified the genes affected only at the exon inclusion level. In the CeA coexpression network, we identified Rab6b, Cdk18 and Igsf21 among the intake-correlated hubs, while in the Area 32, we identified a distinct hub set that included Ppp3r1 and Myeov2. Overall, the data illustrate that excessive ethanol self-administration is associated with broad expression and splicing mechanisms that involve membrane and synapse genes.

Splicing landscape of the eight collaborative cross founder strains.

BACKGROUND: The Collaborative Cross (CC) is a large panel of genetically diverse recombinant inbred mouse strains specifically designed to provide a systems genetics resource for the study of complex traits. In part, the utility of the CC stems from the extensive genome-wide annotations of founder strain sequence and structural variation. Still missing, however, are transcriptome-specific annotations of the CC founder strains that could further enhance the utility of this resource. RESULTS: We provide a comprehensive survey of the splicing landscape of the 8 CC founder strains by leveraging the high level of alternative splicing within the brain. Using deep transcriptome sequencing, we found that a majority of the splicing landscape is conserved among the 8 strains, with ~65% of junctions being shared by at least 2 strains. We, however, found a large number of potential strain-specific splicing events as well, with an average of ~3000 and ~500 with ≥3 and ≥10 sequence read coverage, respectively, within each strain. To better understand strain-specific splicing within the CC founder strains, we defined criteria for and identified high-confidence strain-specific splicing events. These splicing events were defined as exon-exon junctions 1) found within only one strain, 2) with a read coverage ≥10, and 3) defined by a canonical splice site. With these criteria, a total of 1509 high-confidence strain-specific splicing events were identified, with the majority found within two of the wild-derived strains, CAST and PWK. Strikingly, the overwhelming majority, 94%, of these strain-specific splicing events are not yet annotated. Strain-specific splicing was also located within genomic regions recently reported to be over- and under-represented within CC populations. CONCLUSIONS: Phenotypic characterization of CC populations is increasing; thus these results will not only aid in further elucidating the transcriptomic architecture of the individual CC founder strains, but they will also help in guiding the utilization of the CC populations in the study of complex traits. This report is also the first to establish guidelines in defining and identifying strain-specific splicing across different mouse strains.

The genetics of gene expression in complex mouse crosses as a tool to study the molecular underpinnings of behavior traits.

Complex Mus musculus crosses provide increased resolution to examine the relationships between gene expression and behavior. While the advantages are clear, there are numerous analytical and technological concerns that arise from the increased genetic complexity that must be considered. Each of these issues is discussed, providing an initial framework for complex cross study design and planning.

Dual-trait selection for ethanol consumption and withdrawal: genetic and transcriptional network effects.

BACKGROUND: Data from C57BL/6J (B6) × DBA/2J (D2) F2 intercrosses (B6xD2 F2 ), standard and recombinant inbred strains, and heterogeneous stock mice indicate that a reciprocal (or inverse) genetic relationship exists between alcohol consumption and withdrawal severity. Furthermore, some genetic studies have detected reciprocal quantitative trait loci (QTLs) for these traits. We used a novel mouse model developed by simultaneous selection for both high alcohol consumption/low withdrawal and low alcohol consumption/high withdrawal and analyzed the gene expression and genome-wide genotypic differences. METHODS: Randomly chosen third selected generation (S3 ) mice (N = 24/sex/line), bred from a B6xD2 F2 , were genotyped using the Mouse Universal Genotyping Array, which provided 2,760 informative markers. QTL analysis used a marker-by-marker strategy with the threshold for a significant log of the odds (LOD) set at 10. Gene expression in the ventral striatum was measured using the Illumina Mouse 8.2 array. Differential gene expression and the weighted gene co-expression network analysis (WGCNA) were implemented. RESULTS: Significant QTLs for consumption/withdrawal were detected on chromosomes (Chr) 2, 4, 9, and 12. A suggestive QTL mapped to Chr 6. Some of the QTLs overlapped with known QTLs mapped for 1 of the traits individually. One thousand seven hundred and forty-five transcripts were detected as being differentially expressed between the lines; there was some overlap with known withdrawal genes (e.g., Mpdz) located within QTL regions. WGCNA revealed several modules of co-expressed genes showing significant effects in both differential expression and intramodular connectivity; a module richly annotated with kinase-related annotations was most affected. CONCLUSIONS: Marked effects of selection on expression and network structure were detected. QTLs overlapping with differentially expressed genes on Chr 2 (distal) and 4 suggest that these are cis-eQTLs (Chr 2: Kif3b, Kcnq2; Chr 4: Mpdz, Snapc3). Other QTLs identified were on Chr 2 (proximal), 9, and 12. Network results point to involvement of kinase-related mechanisms and outline the need for further efforts such as interrogation of noncoding RNAs.

Effects of repeated alcohol abstinence on within-subject prefrontal cortical gene expression in rhesus macaques.

Male rhesus monkeys (n = 24) had a biopsy of prefrontal cortical area 46 prior to chronic ethanol self-administration (n = 17) or caloric control (n = 7). Fourteen months of daily self-administration (water vs. 4% alcohol, 22 h access/day termed "open-access") was followed by two cycles of prolonged abstinence (5 weeks) each followed by 3 months of open-access alcohol and a final abstinence followed by necropsy. At necropsy, a biopsy of Area 46, contralateral to the original biopsy, was obtained. Gene expression data (RNA-Seq) were collected comparing biopsy/necropsy samples. Monkeys were categorized by drinking status during the final post-abstinent drinking phase as light (LD), binge (BD), heavy (HD) and very heavy (VHD drinkers). Comparing pre-ethanol to post-abstinent biopsies, four animals that converted from HD to VHD status had significant ontology enrichments in downregulated genes (necropsy minus biopsy n = 286) that included immune response (FDR < 9 × 10-7) and plasma membrane changes (FDR < 1 × 10-7). Genes in the immune response category included IL16 and 18, CCR1, B2M, TLR3, 6 and 7, SP2 and CX3CR1. Upregulated genes (N = 388) were particularly enriched in genes associated with the negative regulation of MAP kinase activity (FDR < 3 × 10-5), including DUSP 1, 4, 5, 6 and 18, SPRY 2, 3, and 4, SPRED2, BMP4 and RGS2. Overall, these data illustrate the power of the NHP model and the within-subject design of genomic changes due to alcohol and suggest new targets for treating severe escalated drinking following repeated alcohol abstinence attempts.

Genetic factors involved in risk for methamphetamine intake and sensitization.

Lines of mice were created by selective breeding for the purpose of identifying genetic mechanisms that influence the magnitude of the selected trait and to explore genetic correlations for additional traits thought to be influenced by shared mechanisms. DNA samples from high and low methamphetamine-drinking (MADR) and high and low methamphetamine-sensitization lines were used for quantitative trait locus (QTL) mapping. Significant additive genetic correlations between the two traits indicated a common genetic influence, and a QTL on chromosome X was detected for both traits, suggesting one source of this commonality. For MADR mice, a QTL on chromosome 10 accounted for more than 50 % of the genetic variance in that trait. Microarray gene expression analyses were performed for three brain regions for methamphetamine-naïve MADR line mice: nucleus accumbens, prefrontal cortex, and ventral midbrain. Many of the genes that were differentially expressed between the high and low MADR lines were shared in common across the three brain regions. A gene network highly enriched in transcription factor genes was identified as being relevant to genetically determined differences in methamphetamine intake. When the mu opioid receptor gene (Oprm1), located on chromosome 10 in the QTL region, was added to this top-ranked transcription factor network, it became a hub in the network. These data are consistent with previously published findings of opioid response and intake differences between the MADR lines and suggest that Oprm1, or a gene that impacts activity of the opioid system, plays a role in genetically determined differences in methamphetamine intake.

Utilizing RNA-Seq data for de novo coexpression network inference.

MOTIVATION: RNA-Seq experiments have shown great potential for transcriptome profiling. While sequencing increases the level of biological detail, integrative data analysis is also important. One avenue is the construction of coexpression networks. Because the capacity of RNA-Seq data for network construction has not been previously evaluated, we constructed a coexpression network using striatal samples, derived its network properties and compared it with microarray-based networks. RESULTS: The RNA-Seq coexpression network displayed scale-free, hierarchical network structure. We detected transcripts groups (modules) with correlated profiles; modules overlap distinct ontology categories. Neuroanatomical data from the Allen Brain Atlas reveal several modules with spatial colocalization. The network was compared with microarray-derived networks; correlations from RNA-Seq data were higher, likely because greater sensitivity and dynamic range. Higher correlations result in higher network connectivity, heterogeneity and centrality. For transcripts present across platforms, network structure appeared largely preserved. From this study, we present the first RNA-Seq data de novo network inference.

Selection for drinking in the dark alters brain gene coexpression networks.

BACKGROUND: Heterogeneous stock (HS/NPT) mice have been used to create lines selectively bred in replicate for elevated drinking in the dark (DID). Both selected lines routinely reach a blood ethanol (EtOH) concentration (BEC) of 1.00 mg/ml or greater at the end of the 4-hour period of access in Day 2. The mechanisms through which genetic differences influence DID are currently unclear. Therefore, the current study examines the transcriptome, the first stage at which genetic variability affects neurobiology. Rather than focusing solely on differential expression (DE), we also examine changes in the ways that gene transcripts collectively interact with each other, as revealed by changes in coexpression patterns. METHODS: Naïve mice (N = 48/group) were genotyped using the Mouse Universal Genotyping Array, which provided 3,683 informative markers. Quantitative trait locus (QTL) analysis used a marker-by-marker strategy with the threshold for a significant logarithm of odds (LOD) set at 10.6. Gene expression in the ventral striatum was measured using the Illumina Mouse 8.2 array. Differential gene expression and the weighted gene coexpression network analysis (WGCNA) were implemented largely as described elsewhere. RESULTS: Significant QTLs for elevated BECs after DID were detected on chromosomes 4, 14, and 16; the latter 2 were associated with gene-poor regions. None of the QTLs overlapped with known QTLs for EtOH preference drinking. Ninety-four transcripts were detected as being differentially expressed in both selected lines versus HS controls; there was no overlap with known preference genes. The WGCNA revealed 2 modules as showing significant effects of both selections on intramodular connectivity. A number of genes known to be associated with EtOH phenotypes (e.g., Gabrg1, Glra2, Grik1, Npy2r, and Nts) showed significant changes in connectivity. CONCLUSIONS: We found marked and consistent effects of selection on coexpression patterns; DE changes were more modest and less concordant. The QTLs and differentially expressed genes detected here are distinct from the preference phenotype. This is consistent with behavioral data and suggests that the DID and preference phenotypes are markedly different genetically.

The Collaborative Cross, a community resource for the genetic analysis of complex traits.

The goal of the Complex Trait Consortium is to promote the development of resources that can be used to understand, treat and ultimately prevent pervasive human diseases. Existing and proposed mouse resources that are optimized to study the actions of isolated genetic loci on a fixed background are less effective for studying intact polygenic networks and interactions among genes, environments, pathogens and other factors. The Collaborative Cross will provide a common reference panel specifically designed for the integrative analysis of complex systems and will change the way we approach human health and disease.

Modeling Brain Gene Expression in Alcohol Use Disorder with Genetic Animal Models.

Animal genetic models have and will continue to provide important new information about the behavioral and physiological adaptations associated with alcohol use disorder (AUD). This chapter focuses on two models, ethanol preference and drinking in the dark (DID), their usefulness in interrogating brain gene expression data and the relevance of the data obtained to interpret AUD-related GWAS and TWAS studies. Both the animal and human data point to the importance for AUD of changes in synaptic transmission (particularly glutamate and GABA transmission), of changes in the extracellular matrix (specifically including collagens, cadherins and protocadherins) and of changes in neuroimmune processes. The implementation of new technologies (e.g., cell type-specific gene expression) is expected to further enhance the value of genetic animal models in understanding AUD.

Heritability of serum sodium concentration: evidence for sex- and ethnic-specific effects.

Serum sodium concentration is the clinical index of systemic water balance. Although disordered water balance is common and morbid, little is known about genetic effects on serum sodium concentration at the population level. Prior studies addressed only participants of European descent and either failed to demonstrate significant heritability or showed only modest effect. We investigated heritability of serum sodium concentration in large cohorts reflecting a range of races/ethnicities, including the Framingham Heart Study (FHS, non-Hispanic Caucasian), the Heredity and Phenotype Intervention Heart Study (HAPI, Amish Caucasian), the Jackson Heart Study (JHS, African American), the Strong Heart Family Study (SHFS, American Indian), and the Genetics of Kidney Disease in Zuni Indians Study (GKDZI, American Indian). Serum sodium was transformed for the osmotic effect of glucose, and participants with markedly elevated glucose or reduced estimated glomerular filtration rate (eGFR) were excluded. Using a standard variance components method, incorporating covariates of age, glucose, and eGFR, we found heritability to be high in African American and American Indian populations and much more modest in non-Hispanic Caucasian populations. Estimates among females increased after stratification on sex and were suggestive among female participants in FHS (0.18 ± 0.12, P = 0.057) and male participants in JHS (0.24 ± 0.16, P = 0.067) and statistically significant among female participants in JHS (0.44 ± 0.09, P = 1 × 10 ⁻7), SHFS (0.59 ± 0.05, P = 9.4 × 10⁻46), and GKDZI (0.46 ± 0.15, P = 1.7 × 10⁻4), and male participants in HAPI (0.18 ± 0.12, P = 0.03) and SHFS (0.67 ± 0.07, P = 5.4 × 10⁻²6). Exclusion of diuretic users increased heritability among females and was significant in all cohorts where data were available. In aggregate, these data strongly support the heritability of systemic water balance and underscore sex and ethnicity-specific effects.

Genome-wide and species-wide dissection of the genetics of arthritis severity in heterogeneous stock mice.

OBJECTIVE: Susceptibility to inflammatory arthritis is determined by a complex set of environmental and genetic factors, but only a portion of the genetic effect can be explained. Conventional genome-wide screens of arthritis models using crosses between inbred mice have been hampered by the low resolution of results and by the restricted range of natural genetic variation sampled. The aim of this study was to address these limitations by performing a genome-wide screen for determinants of arthritis severity using a genetically heterogeneous cohort of mice. METHODS: Heterogeneous stock (HS) mice derive from 8 founder inbred strains by serial intercrossing (n>60), resulting in fine-grained genetic variation. With a cohort of 570 HS mice, we performed a genome-wide screen for determinants of arthritis severity in the K/BxN serum-transfer model. RESULTS: We mapped regions on chromosomes 1, 2, 4, 6, 7, and 15 that contain quantitative trait loci influencing arthritis severity at a resolution of a few megabases. In several instances, these regions proved to contain 2 quantitative trait loci: the region on chromosome 2 included the C5 fraction of complement known to be required for K/BxN serum-transfer arthritis but also contained a second adjacent quantitative trait locus, for which an intriguing candidate is Ptgs1 (Cox1). Interesting candidates on chromosome 4 included the Padi family, encoding the peptidyl arginine deiminases responsible for citrulline protein modification; suggestively, Padi2 and Padi4 RNA expression was correlated with arthritis severity in HS mice. CONCLUSION: These results provide a broad overview of the genetic variation that controls the severity of K/BxN serum-transfer arthritis and suggest intriguing candidate genes for further study.

A loss-of-function nonsynonymous polymorphism in the osmoregulatory TRPV4 gene is associated with human hyponatremia.

Disorders of water balance are among the most common and morbid of the electrolyte disturbances, and are reflected clinically as abnormalities in the serum sodium concentration. The transient receptor potential vanilloid 4 (TRPV4) channel is postulated to comprise an element of the central tonicity-sensing mechanism in the mammalian hypothalamus, and is activated by hypotonic stress in vitro. A nonsynonymous polymorphism in the TRPV4 gene gives rise to a Pro-to-Ser substitution at residue 19. We show that this polymorphism is significantly associated with serum sodium concentration and with hyponatremia (serum sodium concentration < or =135 mEq/L) in 2 non-Hispanic Caucasian male populations; in addition, mean serum sodium concentration is lower among subjects with the TRPV4(P19S) allele relative to the wild-type allele. Subjects with the minor allele were 2.4-6.4 times as likely to exhibit hyponatremia as subjects without the minor allele (after inclusion of key covariates). Consistent with these observations, a human TRPV4 channel mutated to incorporate the TRPV4(P19S) polymorphism showed diminished response to hypotonic stress (relative to the wild-type channel) and to the osmotransducing lipid epoxyeicosatrienoic acid in heterologous expression studies. These data suggest that this polymorphism affects TRPV4 function in vivo and likely influences systemic water balance on a population-wide basis.

Brain gene expression differences related to ethanol preference in the collaborative cross founder strains.

The collaborative cross (CC) founder strains include five classical inbred laboratory strains [129S1/SvlmJ (S129), A/J (AJ), C57BL/6J (B6), NOD/ShiLtJ (NOD), and NZO/HILtJ (NZO)] and three wild-derived strains [CAST/EiJ (CAST), PWK/PhJ (PWK), and WSB/EiJ (WSB)]. These strains encompass 89% of the genetic diversity available in Mus musculus and ∼10-20 times more genetic diversity than found in Homo sapiens. For more than 60 years the B6 strain has been widely used as a genetic model for high ethanol preference and consumption. However, another of the CC founder strains, PWK, has been identified as a high ethanol preference/high consumption strain. The current study determined how the transcriptomes of the B6 and PWK strains differed from the 6 low preference CC strains across 3 nodes of the brain addiction circuit. RNA-Seq data were collected from the central nucleus of the amygdala (CeA), the nucleus accumbens core (NAcc) and the prelimbic cortex (PrL). Differential expression (DE) analysis was performed in each of these brain regions for all 28 possible pairwise comparisons of the CC founder strains. Unique genes for each strain were identified by selecting for genes that differed significantly [false discovery rate (FDR) < 0.05] from all other strains in the same direction. B6 was identified as the most distinct classical inbred laboratory strain, having the highest number of total differently expressed genes (DEGs) and DEGs with high log fold change, and unique genes compared to other CC strains. Less than 50 unique DEGs were identified in common between B6 and PWK within all three brain regions, indicating the strains potentially represent two distinct genetic signatures for risk for high ethanol-preference. 338 DEGs were found to be commonly different between B6, PWK and the average expression of the remaining CC strains within all three regions. The commonly different up-expressed genes were significantly enriched (FDR < 0.001) among genes associated with neuroimmune function. These data compliment findings showing that neuroimmune signaling is key to understanding alcohol use disorder (AUD) and support use of these 8 strains and the highly heterogeneous mouse populations derived from them to identify alcohol-related brain mechanisms and treatment targets.