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Keywords:

  • Behavioral sensitization;
  • cocaine;
  • dual diagnosis;
  • gene expression;
  • hippocampus;
  • microarray;
  • nucleus accumbens;
  • prefrontal cortex;
  • schizophrenia;
  • striatum

Abstract

  1. Top of page
  2. Abstract
  3. Materials and methods
  4. Results
  5. Discussion
  6. References
  7. Acknowledgements
  8. Supporting Information

Cortical–striatal circuit dysfunction in mental illness may enhance addiction vulnerability. Neonatal ventral hippocampal lesions (NVHL) model this dual diagnosis causality by producing a schizophrenia syndrome with enhanced responsiveness to addictive drugs. Rat genome-wide microarrays containing >24 000 probesets were used to examine separate and co-occurring effects of NVHLs and cocaine sensitization (15 mg/kg/day × 5 days) on gene expression within medial prefrontal cortex (MPFC), nucleus accumbens (NAC), and caudate-putamen (CAPU). Two weeks after NVHLs robustly amplified cocaine behavioral sensitization, brains were harvested for genes of interest defined as those altered at P < 0.001 by NVHL or cocaine effects or interactions. Among 135 genes so impacted, NVHLs altered twofold more than cocaine, with half of all changes in the NAC. Although no genes were changed in the same direction by both NVHL and cocaine history, the anatomy and directionality of significant changes suggested synergy on the neural circuit level generative of compounded behavioral phenotypes: NVHL predominantly downregulated expression in MPFC and NAC while NVHL and cocaine history mostly upregulated CAPU expression. From 75 named genes altered by NVHL or cocaine, 27 had expression levels that correlated significantly with degree of behavioral sensitization, including 11 downregulated by NVHL in MPFC/NAC, and 10 upregulated by NVHL or cocaine in CAPU. These findings suggest that structural and functional impoverishment of prefrontal-cortical-accumbens circuits in mental illness is associated with abnormal striatal plasticity compounding with that in addictive disease. Polygenetic interactions impacting neuronal signaling and morphology within these networks likely contribute to addiction vulnerability in mental illness.

People with schizophrenia suffer from substance disorders at rates 2–6 times greater than the general population increasing medical and psychiatric morbidity and mortality, financial destitution, homelessness and risk of incarceration (Dixon 1999; Kessler 2004; Miller et al. 2006; O Brien et al. 2004). Investigating how the neural substrates of mental illness and drug reinforcement interact to accentuate the addiction process will be important in preventing and improving treatments for addictions and dual diagnosis syndromes (Chambers et al. 2001). Experiments that combine animal models of mental illness with addiction paradigms suggest that developmental abnormalities involving the amygdala and/or hippocampus produce secondary changes in prefrontal cortical–striatal networks that alter motivational and behavioral responses to addictive drugs (Chambers 2007; Chambers et al. 2007). Neonatal Ventral Hippocampal Lesions (NHVL) in rats, in addition to producing positive-like, negative and cognitive symptoms of schizophrenia and other developmental, pharmacological and neurobiological attributes of this disorder (Lipska et al. 1993; Tseng et al. 2009), show elevated patterns of cocaine (Chambers & Self 2002) and methamphetamine self-administration (Brady et al. 2008), enhanced reward-motivated impulsivity (Chambers et al. 2005), and augmented behavioral sensitization to cocaine (Chambers & Taylor 2004).

Recent studies have examined the interactive effects of NVHL and a behaviorally sensitizing cocaine history (–Hx) on prefrontal cortical–striatal circuits. Although neither NVHL nor cocaine-Hx, separately or in combination, alter cocaine-stimulated dopamine (DA) efflux into the Nucleus Accumbens (NAC) or Caudate-Putamen (CAPU) (Chambers et al. 2010b), they do impact cortical–striatal networks postsynaptic to DA afferents (Chambers et al. 2010a). Specifically, altered patterns of neural activation due to NVHL and cocaine-Hx compound one another when co-occurring, leading to amplified neural activation in the CAPU and abnormally high levels of long-term behavioral sensitization (Chambers et al. 2010a).

The present study examines molecular changes that contribute to altered cellular phenotypes and neural network dynamics within the Medial Prefrontal Cortex (MPFC), NAC and CAPU that may underpin interactions of the NVHL-schizophrenia and cocaine sensitization models. Gene expression was analyzed two weeks after NVHL and SHAM-operated controls experienced cocaine behavioral sensitization (cocaine-Hx) or control saline injections. We examined how NVHL and cocaine-Hx impacted gene expression by region and directionality of change, and the extent to which significant expression changes were correlated with previously quantified phenotypes of behavioral sensitization. Secondary analyses explored the functional and nervous system disease-related associations of significantly altered genes, followed by RT-PCR confirmations of microarray expression trends.

Materials and methods

  1. Top of page
  2. Abstract
  3. Materials and methods
  4. Results
  5. Discussion
  6. References
  7. Acknowledgements
  8. Supporting Information

Animals

Male Sprague-Dawley pups, born in our facility underwent neonatal surgeries on Postnatal Day (PD)-7 as previously described (Chambers & Lipska 2011). Ibotenic acid (NVHL: 3.0 µg in 3.0 µl artificial CSF) or aCSF only (SHAMS) was delivered into the ventral hippocampus bilaterally (AP −3.0, L ±3.5, DV −5.0 mm) (Lipska et al. 1993) under hypothermic anesthesia. To create a balanced distribution of maternal genetic and environmental rearing contributions from 10 source litters to the four experimental groups, while anticipating inaccurate NVHL surgeries, the following protocol was implemented: First, six pups from each mother were chosen for surgery, (two SHAM, four NVHL) with culling of litters to these pups only. Second, upon weaning (PD 21), the two SHAMs were co-housed, with one rat assigned to cocaine and the other saline. Meanwhile, one pair of co-housed lesioned rats was assigned to cocaine and the other pair to saline. Third, all six rats were carried through behavioral testing, tissue harvesting, and lesion verification, at which time only two of the four lesioned rats (one NHVL-SAL, one NVHL-COC) were selected for inclusion in the study as determined by histological assessment of best-of-two lesion accuracy. All procedures accorded with the NIH Guide for Care and Use of Laboratory Animals, and the Indiana University Animal Care and Use Committee.

Cocaine exposure and behavior

On PD 60, rats were randomized to 5 days of once daily i.p. injections of cocaine [15 mg/kg (NIDA) in 1 ml/kg saline] or saline (1 ml/kg) in 43 × 43 cm locomotor arenas as previously described (Chambers et al. 2010a). Locomotor distance was measured during 2-h sessions with injections delivered after 60 min.

Tissue harvesting and lesion verification

After injections, rats were housed undisturbed for 2 weeks until being killed (PD 78: decapitation under brief isoflurane) and brain harvesting. A Brinkman tissue chopper was used to make 2 mm coronal sections (approximately 4.7–2.7 and 2.7–0.7 mm from Bregma) from which MPFC, NAC and CAPU regions were dissected (Fig. 1a). Regions of interest were delineated to allow fast, reproducible dissection of fresh brain and to capture tissue from regions previously analyzed in parallel studies of the NVHL model in cocaine sensitization using microdialysis (Chambers et al. 2010b) and c-Fos labeling (Chambers et al. 2010a). Bilateral samples were pooled and homogenized in TRIzol (Invitrogen, Carlsbad, CA, USA) with augmented TRIzol concentrations used according to our established protocol (Edenberg et al. 2005). Following RNA-isolation by ethanol precipitation, samples were purified on RNeasy columns (Qiagen, Hilden, Germany) and stored at −80°C until microarray analysis. Caudal brains were frozen in isopentane for later lesion verification. Time from decapitation to tissue homogenization was <2 min.

image

Figure 1. Histological maps. (a) Tissue dissections for microarray analysis are depicted superimposed on coronal maps at approximate coordinates (mm) rostral from Bregma. (b) Compilation of lesion extent maps on sections caudal from Bregma (on left) show largest (black) vs. smallest (white within largest) extents of lesions of rats (n = 19) qualifying for the study. The two micrographs (on right) show examples of coronal sections from actual SHAM vs. NVHL rats. A larger than average qualifying lesion is shown for visual clarity.

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For lesion verification, caudal brains were cryostat-cut (40 µm sections per 400 µm through the hippocampus) and thionine stained (Chambers & Lipska 2011). Lesion accuracy was rated upon visualization of bilateral changes to the ventral hippocampus (structural atrophy/ventricular enlargement/paucity or disarray of cellular nuclei and layers) without direct involvement of adjacent structures (dorsal hippocampus, thalamus, amygdala, temporal cortex) (Chambers & Lipska 2011; Lipska et al. 1993) (Fig. 1b). Lesioned brains rated as inferior were excluded from the study. A total of 10 litters contributed to four experimental groups of 9–10 rats each, with progeny from the same set of eight mothers represented in every group (Table S1a).

Microarray analysis

RNA samples were labeled using the standard protocol for the Ambion WT Expression kit combined with the Affymetrix GeneChip® WT Terminal Labeling and Controls Kit. Individual labeled samples were hybridized to the Rat Gene 1.0 ST GeneChips® for 17 h then washed, stained and scanned with the standard protocol using Affymetrix GeneChip® Command Console Software (AGCC) to generate data (CEL files). Samples for each brain region were processed separately in two batches per region, balancing the four experimental groups in each batch. Arrays were visually scanned for abnormalities or defects; none were found. CEL files were imported into Partek Genomics Suite (Partek, Inc., St. Louis, Mo, USA). Summarized signals for each probe set were log2 transformed. Log-transformed signals were used for principal components analysis, hierarchical clustering and signal histograms to determine if there were any outlier arrays; none were detected. Untransformed RMA (Robust Multi-array Average) (Bolstad et al. 2003) signals were used for fold change calculations. RMA signals were generated for 27 432 core probesets using the RMA background correction, quantile normalization and summarization by median polish. A histogram of log2-transformed RMA signals revealed an inflection point just below 4.5 indicating the peak of nondetectable probesets. On the basis of this analysis and because removing genes not expressed improves analysis (Mcclintick & Edenberg 2006), we removed approximately 3000 probesets in each brain region with log2 expression levels <4.5. To identify differentially expressed genes, anovas were applied to each region separately using independent factors of lesion status, drug history, litter of origin and labeling batch. We then determined Least Squares Mean expression levels, fold changes (untransformed RMA), P-values (due to litter, NVHL, cocaine-Hx, and NVHL × cocaine-Hx interaction), and false discovery rates (FDR) (Storey & Tibshirani 2003). As there is no sequence data available for Sprague-Dawley rats, probesets with SNPs were not identified.

Genes affected by NVHL and cocaine-Hx (P < 0.01) were first examined for overlap with gene sets showing decreasing P-values for an effect of litter of origin which reflects natural expression variation. Then, genes affected by NVHL and cocaine-Hx at P < 0.001 were examined in χ2 analysis to determine how their proportions varied by region of interest and directionality of change. These genes were then examined across subjects (irrespective of lesion status or drug-Hx) in Pearson correlations between microarray expression levels and degree of behavioral sensitization (day 5, postinjection locomotion). These correlations included all SHAM-SAL, SHAM-COC and NVHL-COC rats (N = 28). NVHL-SAL (N = 10) rats were excluded from this analysis since their NVHL phenotypes were not expressed in the locomotor paradigm (i.e., they never received a psychostimulant required to express the NVHL phenotype). All P < 0.001 genes were investigated for function and disease association using Ingenuity Pathway Analysis (Ingenuity Systems, www.ingenuity.com) as well as via a literature search.

Quantitative RT-PCR

Real-time PCR was used to confirm results for 15 genes: five named genes from each region with the highest fold differences (for either NVHL or cocaine-Hx main effects) for which PCR probes were available. From collected samples, 1.5 µg of total RNA was reverse transcribed using random primers and the High Cap cDNA RT Kit (Life Technologies). Primers were selected from Life Technologies catalog of Taqman® Gene Expression Assays (http://bioinfo.appliedbiosystems.com/genome-database/gene-expression.html). In most cases the recommended primer for a particular gene was selected. Gapdh was used for the control as it was stable in all three regions. RT-PCR was performed in triplicate for all of the samples using the TaqMan Fast Advanced Master Mix (Life Technologies), using 2% of the cDNA for each reaction on a StepONE instrument (Applied Biosystems, Carlsbad, CA, USA). The mean CT of the three replicates for Gapdh for each sample was subtracted from the mean CT for each gene to yield the Delta CT (relative expression level) for each gene.

Results

  1. Top of page
  2. Abstract
  3. Materials and methods
  4. Results
  5. Discussion
  6. References
  7. Acknowledgements
  8. Supporting Information

Behavioral sensitization

Cocaine injections increased locomotion from day 1 to 5 in the 10-min postinjection intervals (Fig. 2a) and over the whole hour of postinjection activity (Fig. 2b). Repeated measures anova (day 1 vs. day 5) confirmed robust behavioral sensitization [day × drug: F(1,34) = 23.0, P < 0.001] that interacted with NVHL to accentuate activation [day × drug × lesion: F(1,34) = 4.7, P < 0.05]. These effects were superimposed on overall main effects and interactions of NVHL and cocaine sensitization [lesion: F(1,34) = 5.9, P < 0.05; drug: F(1,34) = 56.1, P < 0.001; lesion x drug: F(1,34) = 6.4, P < 0.05].

image

Figure 2. Behavioral sensitization to cocaine. (a) Distance ambulated over the postinjection hour on day 1 and day 5 broken into 6 × 10 min bins. (b) Total post-injection activity depicted according to lesion status (NVHL or SHAM) and cocaine (COC) or saline (SAL) treatment. Significance levels from Rep Measures anova: *P < 0.05, ***P < 0.001. Data are presented as means with error bars representing ±SEM. (SHAM-SAL, n = 9; NVHL-SAL, n = 10; SHAM-COC, n = 10; NVHL-COC, n = 9).

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Patterns of gene expression changes

Between 87 and 89% of the probesets in each region were reliably detected on the arrays [log2(RNA ≥ 4.5)] and analyzed showing similar relative proportions of genes effected by NVHL vs. cocaine-Hx at P < 0.01 and P < 0.001 significance levels (Table S1b). The lowest FDR ranges of significantly altered genes were produced by NVHL in the NAC region (Table S1c). Genes impacted by NVHL, cocaine-Hx and their interactions at P < 0.01 (Table S2) generally showed increasing concentrations within gene sets that showed increasing levels of significance of natural variation in expression (P-values of the litter factor), with the exception of cocaine-Hx effect genes in the MPFC (Fig. 3a). In the MPFC, over 50% of all genes impacted by NVHL (P < 0.01) were found among the top 25% most naturally variable (according to P-value of litter). In both NAC and CAPU, over half of cocaine-Hx genes (P < 0.01) were found in the top 25% most natural variables.

image

Figure 3. Patterns of gene expression due to NVHL vs. cocaine-Hx effects. (a) In each brain region, genes were filtered into increasingly smaller sets according to the significance thresholds (P-values on x-axis) of natural variation in expression that occurred due to litter of origin; the % of genes in these subsets that also showed expression change due to NVHLs or COC-Hx (at P < 0.01) generally increases with increasing filtering. (b) The distribution of gene changes produced by NVHL and COC-Hx at P < 0.001 is depicted graphically in relative proportions as pie charts with differential area sizes that reflect the number of genes (stated within) changed by effect and region, and slices areas that reflect the proportion of upregulation (white) vs. downregulation (dark). Gene expression changes were assessed the same subject groups analyzed behaviorally in Fig. 2. (SHAM-SAL, n = 9; NVHL-SAL, n = 10; SHAM-COC, n = 10; NVHL-COC, n = 9).

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The proportion of gene expression differences (at P < 0.001) varied significantly by treatment [χ2(2, N = 135) = 51.7, P < 0.001] such that NVHL impacted twofold more genes than cocaine-Hx, and fourfold more than those impacted as lesion × drug interactions (Table 1a). The overall number of genes impacted also varied by region [χ2(4, N = 135) = 20.2, P < 0.001], such that NVHL, cocaine-Hx and their interactions collectively impacted the most genes in the NAC, where 50% of all P < 0.001 gene changes occurred.

Table 1. Distribution of NVHL and cocaine-Hx genes (P < 0.001) (a) by region (N(%)); (b) by direction of change and region [N (%)]; and (c) with expression levels correlating with behavioral sensitization (Pearson; P < 0.05)
(a)
 MPFCNACCAPU 
NVHL13 (16)51 (61)19 (23)83 (100)
COC-Hx8 (23)11 (31)16 (46)35 (100)
NVHL × COC-Hx9 (53)5 (29)3 (18)17 (100)
 306738135
(b)
 NVHL COC-Hx  
 DownUpDownUp 
MPFC9 (43)4 (19)3 (14)5 (24)21 (100)
NAC35 (56)16 (26)5 (8)6 (10)62 (100)
CAPU5 (14)14 (40)5 (14)11 (31)35 (100)
 49341322118
(c)
RegionDirectionN (% of P < 0.001 genes) correlating with behavior
  NVHLCOC-Hx
MPFCDown3 (33)1 (33)
 Up1 (25)2 (40)
NACDown13 (37)1 (20)
 Up3 (19)0 (0)
CAPUDown1 (20)0 (0)
 Up8 (576 (55)

The directionality of gene expression changes differed by region and treatment (Fig. 3b). Whereas most genes changed in MPFC and NAC were downregulated (57% and 64%, respectively), most altered in the CAPU (71%) were upregulated [χ2(2, N = 118) = 11.8, P < 0.01] (Table 1b). A predominance of downregulated genes produced by NVHL contrasted significantly with a predominance of upregulated genes due to cocaine-Hx [χ2(1, N = 118) = 4.7, P < 0.05]. For genes impacted by NVHL, a regional variation in the direction of change was also identified [χ2(2, N = 83) = 10.9, P < 0.05] with more genes downregulated in MPFC and NAC (outnumbering upregulated genes 2:1) contrasting with a preponderance of upregulated genes in CAPU (3:1 over downregulated genes).

None of the 118 genes with expression changes (P < 0.001) due to NVHL or cocaine-Hx, were changed in the same direction by both treatments. None of the 83 genes impacted by NVHL or cocaine-Hx in either MPFC or NAC were affected in both regions. Similarly, none of the 56 genes altered by NVHL or cocaine-Hx in either MPFC or CAPU were altered in both regions. Only one gene out of 69 impacted by NVHL in either the NAC or CAPU was impacted (Cd 180, upregulated) in both regions, and only one of 26 impacted by cocaine-Hx in either region was affected (Mettl 11b, upregulated) in both.

Behavioral correlations and functional associations of genes of interest

Genes impacted by NVHL or cocaine-Hx (P < 0.001) with expression levels that correlated significantly with degree of behavioral sensitization (Pearson; P < 0.05), occurred most frequently where NVHL and cocaine-Hx had their strongest effects by region and directionality of change (Table 1c). Over a third of NVHL-induced downregulations in the MPFC and NAC were significantly inversely correlated with behavioral sensitization; over half of all probesets upregulated by NVHL or cocaine-Hx in the CAPU were positively correlated with behavioral sensitization. The subset of named genes that had significant correlations with behavioral sensitization is listed in Table 2.

Table 2. Identification and function of NVHL and cocaine-Hx genes (P < 0.001) by region
Gene symbolProbe setNameFold changeP valueBehavior Correlation (p)Function**
  1. Behavioral correlation (p): Yes (Y) or No (N) shows P values of the Pearson correlation between microarray gene expression and degree of behavioral sensitization

  2. *Genes included in RT-PCR confirmation analysis.

  3. **Numbers denote where genes are described within Ingenuity functional categories: (1) amino acid metabolism, (2) cell to cell signaling and interaction, (3) cell morphology, (4) nervous system development and function, (5) neurological disorder, (6) psychological disorder and (7) behavior (with functional specifics or diseases associations listed).

MPFC-NVHL (10 named of 13 probesets detected)      
Tmem9210746449Transmembrane protein 92−1.151.52E−04Y (0.007) 
Il13ra1*10936335Interleukin 13 receptor alpha11.148.74E−04N2 (Cell binding)
Dnah8*10832122Dynein axonemal heavy chain 8−1.119.56E−04N 
Ccdc58*10754401Coiled-coil domain contain 581.119.70E−04Y (0.044) 
Esr210890654Estrogen receptor 2−1.103.37E−04Y (0.047)2,3,4,5,6,7 (Synaptic plasticity, memory, psychosis, bipolar, aggression, fear)
Odf3*10712116Outer dense fiber sperm tails 3−1.098.06E−04N 
Zfhx210783759Zinc finger homeobox 2−1.082.83E−04Y (0.046) 
Hydin10807939Hydrocephalus inducing1.084.47E−04N 
Ccdc4910746766Coiled-coil domain contain 58−1.067.85E−04N 
Pask10929995PAS domain contain ser/threo kin−1.068.97E−04N 
MPFC-COC (3 named of 8 probesets)      
Gfap*10747948Glial fibrillary acidic protein−1.141.40E−04N2,3,4,5,6 (Astrocyte activation, synaptic loss, major depression, Parkinson's)
Mthfs10904377Methenyltetrahydrofolate synthetase1.089.54E−04Y (0.022)1(L-tetrahydrofolic acid metabolism)
Ptk210904377Protein tyrosine kinase 21.043.48E−04Y (0.046)2,3,7 (Morphology of cytoskeleton, cell protrusions, nursing)
NAC-NVHL (29 named of 51 probesets)      
ND610930618NADH dehydrogenase subunit 61.171.69E−04N 
Cd180*10812775CD180 molecule1.176.33E−04N2 (Activation of immune cells)
V1rf2*10718387Vomeronasal 1 receptor F2−1.161.74E−04Y (0.007) 
Cxcl9*10771660Chemokine (CXC motif) ligand 9−1.159.17E−04Y (0.004)2,3,4 (Activation/binding of immune and cancer cells, microglia chemotaxis)
Olr378*10729055Olfactory receptor 378−1.148.44E−04N 
Krt2310747113Keratin 23 histone deacetylase induce−1.142.12E−04Y (0.009) 
Hnf4a10842081Hepatocyte nuclear factor 4 alpha−1.137.59E−04N1,2 (Metabolism of L-ornithine, immune cell activation)
Muc410754735Mucin 4, cell surface associated−1.133.21E−06Y (0.014)2,3 (Binding and morphology of cancer cell lines)
Lyl110810064Lymphoblastic leukemia derived seq 1−1.131.28E−04Y (0.021) 
Cd4010842883CD 40 molecule TNF receptor Superfam5−1.133.67E−04N2,3,5 (Activation of immune cells, morphology of cancer cells, HIV encephalopathy)
P2ry1210823365Purinergic recpt.P2Y G-protien coupled121.132.32E−04N2,3 (Activation, binding, shape of blood cells)
Gpr3410936742G-prot. coupled receptor 341.122.20E−05N 
Olr49310846972Olfactory receptor 493−1.121.40E−04Y (0.009) 
Sat110933716Spermidine/spermine N1-acytltnsfrase11.122.19E−04N 
Tuft110824844Tuftelin 1−1.126.49E−05N 
Ccdc6710915107Coiled-coil domain containing 67−1.119.46E−04N 
Ppp4r110930285Protein phosphatase 4, reg subunit1−1.118.41E−04N 
Plcd310747985Phospholipase C, delta 3−1.095.60E−04N 
Dom3z10831373DOM-3 homolog Z−1.089.75E−04N 
Senp310744143SUMO1/sentrin/SMT3 peptidase31.083.40E−05N 
Arhgef310786338Rho guanine nucleotide exchge fact3−1.089.34E−04N 
Sds10762324Serine dehydratase−1.089.46E−04Y (0.007) 
Zdhhc210791935Zinc finger DHHC-type containing 21.074.00E−04Y (0.032)2 (Cell to cell contact of cancer cell lines)
Gpr17710819975G-protein-coupled receptor 1771.072.25E−04Y (<0.001) 
Prim210927213Primase DNA polypeptide 21.077.60E−04N 
Jmjd610749352Jumonji domain contain 6−1.078.58E−04N2 (Activation of immune cells)
Surf619843870Surfeit 6−1.078.13E−05Y (0.015) 
Cpsf410760173Cleavage and polyadenylation sp fact41.068.08E−05N 
Psma510818317Proteasome subunit alpha type 51.068.19E−04Y (0.026) 
NAC-COC (8 of 11)      
Mettl11b*10769436Methyltransferase like 11b1.189.54E−05N 
Zbtb4510704281Zinc finger and BTB domain cont45−1.115.76E−05N 
Foxp410921408Forkhead box P4−1.095.28E−05N 
Lppr210908562Lipid phosphate phosphatase protein. typ2−1.065.43E−05N 
Fgd210828863FYVE RhoGEF and PH domain cont.21.069.32E−04N 
Prkaa210878416Prot. kin. AMP-activated alpha2 cat. sub.−1.059.89E−04N3 (Morphology of red blood cells)
Rpl3210915968Ribosomal protein L321.032.49E−04N 
Cts710793624Cathespin 71.049.79E−04N 
CAPU-NVHL (12 of 19)      
Cd180*10812775Cd180 molecule1.174.89E−05Y (0.037)2 (Activation of immune cells)
Klf2*10790670Kruppel-like factor 2−1.155.09E−04N3 (Morphology of endothelial and blood cells)
V1rg13*10719078Vomeronasal 1 receptor G131.155.04E−04Y (0.026) 
Adam410890964A disintegrin metalloprotease domain 41.099.87E−04N 
Adamts510752852ADAM metallopeptidase thrombospon 1−1.088.07E−04N 
Fkbp210728312FK506 binding protein 21.082.40E−04N 
Lipe10705184Lipase, hormone sensitive1.08.60E−04N3 (Morphology of reproductive cells)
Cpne310875680Copine II1.086.45E−04Y (0.024) 
Raver210870240Ribonucleoprotein, PTB-binding 21.075.83E−04Y (0.007) 
Dnajb110810295DnaJ (Hsp40) h-log subfam.B. mem1−1.076.88E−04N5 (Huntington disease, encephalopathy)
Hmgn110753348High-mobility grp. nucleosome bnd. dom11.068.42E−04N3 (Cell repair)
Pdxp10897524Pyridoxal (pyridoxine, vit B6) phosptse−1.064.05E−04N 
CAPU-COC (13 of 16)      
Mettl11b*10769436Methyltransferase like 11B1.147.77E−04N 
Als2cr12*10928290Amyotropic lat. sclerosis 2 (juv) chrom.1.103.14E−04Y (0.024) 
Pramel610837530Preferent. exp. Antigen melanoma like61.099.94E−04N 
Scgb3a110733134Secretoglobin fam. 3A mem.11.083.17E−04N 
Nat110791279N-acetyltransferase 1(arylamine N-acTN)1.087.71E−04Y (0.001) 
Slitrk310823672SLIT and NTRK-like fam. Mem.3−1.069.61E−04N 
Znf57410705100Zinc finger protein 574−1.069.56E−04N 
Ech110705631Enoyl coenzyme A hydratase 1, peroxi.1.067.56E−04Y (0.011) 
Rps2610767371Ribosomal protein S261.065.97E−04Y (0.003) 
Rps2610934500Ribosomal protein S261.053.01E−04Y (0.005) 
Rps2610899868Ribosomal protein S261.054.51E−04Y (0.002) 
Tdg10901458Thymine-DNA glycosylase−1.054.10E−04N 
Ywhab10842052Tyros. 3-m-oxygenase/tryptophan 5-m act−1.038.11E−04N 

Among the 75 probesets representing known genes impacted by NVHL or cocaine-Hx (P < 0.001), Ingenuity Pathways analysis showed that ‘cell to cell signaling and interaction’ and ‘cell morphology’ were the most frequently represented among the seven categories related to neuronal function and neuropsychiatric diseases, (associated with 13 and 11 genes respectively), while ‘neurological disorders’ and ‘nervous system development and function’ were the third and fourth most represented categories (5 and 4 genes respectively) (Table 2). Expression levels of 27 of these genes were significantly correlated with degree of behavioral sensitization. Eleven of the 15 genes changed due to NVHLs in either the MPFC or NAC that were significantly correlated with behavioral sensitization, were inversely correlated. In contrast, all 10 genes in the CAPU showing expression changes due to NVHL or cocaine-Hx that also correlated significantly with degree of behavioral sensitization, were positive correlations. A total of 7 genes of interest (Esr2, Mthfs, Ptk2, Cxcl9, Muc4, Zdhhc2, CD180) were changed by NVHL or cocaine-Hx at P < 0.001, had expression levels that correlated with degree of behavioral sensitization, and were identified by Ingenuity analysis as having neural functions including but not limited to ‘cell to cell signaling and interaction’ for six of these genes.

RT-PCR confirmations

For each of the 15 genes undergoing PCR confirmation (five genes per region denoted in Table 2), four different comparisons were assessed including those indicating NVHL-induced changes [(NVHL-SAL/SHAM-SAL) and (NVHL-COC/SHAM COC)] and cocaine-Hx-induced changes [(NVHL-COC/NVHL-SAL) and (SHAM-COC/SHAM-SAL)] generating a total of 60 points to correlate between PCR and Microarray. A significant overall concurrence (r = 0.26; P < 0.05) between relative quantity ratio (PCR) and fold change (Microarray) was present producing a regression line (m = 0.37, b = 0.03). This overall correlation was carried most strongly by the correlation between the 20 comparisons (five genes, four comparisons each) drawn from the CAPU region (r = 0.836, P < 0.001; m = 1.02, b = 0.06).

Discussion

  1. Top of page
  2. Abstract
  3. Materials and methods
  4. Results
  5. Discussion
  6. References
  7. Acknowledgements
  8. Supporting Information

This is the first rat-genome microarray analysis of mRNA expression in cortical–striatal circuits in the NVHL model, and the first to examine co-occurring effects of a mental illness model and addictive drug exposure. A key advantage of the NVHL model here is that it potentiates behavioral sensitization to addictive drugs, providing a view on molecular contributions to network dysfunction in mental illness that might increase addiction vulnerability. The potentiation of cocaine behavioral sensitization observed here is reliable in the NVHL model (Chambers & Taylor 2004; Chambers et al. 2010a,b). NVHL-amplification of behavioral sensitization also occurs with other addictive drugs abused at high rates in schizophrenia including ethanol (Conroy et al. 2007) and nicotine (Berg & Chambers 2008), paralleling increased self-administration of cocaine (Chambers & Self 2002) and ethanol (Berg et al. 2011) in NVHL rats.

We examined differences in gene expression 2 weeks after cocaine treatment to detect long-lasting changes linked with behavioral sensitization and addiction rather than intoxication/withdrawal. Recent studies using exactly the same cocaine dosing regimen used here, but with a cocaine challenge after 2 weeks, shows that NVHL rats maintain abnormal elevations in behavioral sensitization (Chambers et al. 2010a,b) indicating that the molecular data reported here correspond to this enduring behavioral abnormality. Unsurprisingly, the overall impact of NVHL was greater than cocaine-Hx, altering the expression of more genes in every region, and 2-fold more overall (Table 1a). Similarly, NVHLs reduce brain volumes in MPFC and NAC, with increased cell packing densities, while a cocaine regimen identical to the present study has no such effects (Chambers et al. 2010a).

NVHL and cocaine-Hx effects on gene expression were distributed differentially across the regions. Quantities of genes impacted by cocaine-Hx across MPFC, NAC and CAPU regions increased modestly (but non-significantly) following a rostral-to-caudal gradient in ratios of 1:1.5:2. Similarly, while acute cocaine doses of 15 mg/kg increase DA concentrations >300% in all three of these regions (Chambers et al. 2010b; Sorg & Kalivas 1993), many of the enduring neural adaptations underlying locomotor sensitization and habit formation may be represented most robustly in the striatum following a rostral-to-dorsal-caudal gradient (Chambers et al. 2010a; Everitt & Robbins 2005; Willuhn & Steiner 2006). In contrast to cocaine-Hx, NVHL produced a disproportionally larger impact in the NAC affecting about 3-fold more genes than in MPFC or CAPU. This may reflect how the NAC, unlike MPFC or CAPU, bears the consequences of ventral hippocampal damage via two converging anatomical pathways, one directly from ventral hippocampus (Kelley & Domesick 1982), and the other di-synaptically from hippocampus to MPFC to NAC (O'Donnell & Grace 1995; Pennartz et al. 1994). Somewhat unexpectedly NVHL impacted slightly more genes in CAPU than in MPFC, even though the ventral hippocampus projects more directly to the MPFC. This finding may reflect a richer diversity of cell classes in the MPFC than the striatum, worsening the noise-to-signal ratio of expression changes.

NVHLs predominantly reduced gene expression in MPFC and NAC, but mostly increased expression in CAPU where cocaine-Hx also had its strongest, mostly upregulatory effect (Fig. 3b). These patterns mirror prior findings where two weeks after the same cocaine dosing, acute cocaine injections produced both (a) decreased neural activation in the MPFC of NVHL rats with increased activation in the CAPU, and (b) increased activation in the CAPU of SHAM rats with prior cocaine-Hx(Chambers et al. 2010a). NVHL rats show abnormal physiological responses to DA and glutamate-mediated stimulation involving pyramidal and medium spiny neurons within the MPFC and NAC (Goto & O'Donnell 2002; O'Donnell et al. 2002; Tseng et al. 2006; Tseng et al. 2007) corresponding to NVHL-induced atrophy and loss of dendritic complexity and spines in MPFC and NAC neurons (Alquicer et al. 2008; Flores et al. 2005). In contrast, chronic cocaine produces abnormal growth of these same morphological parameters in these same regions (Robinson & Kolb 1999). Together, these findings suggest that patterns of higher vs. lower gene expression in the present study represent molecular underpinnings of the morphological and functional pathologies within cortical–striatal networks generated by NVHL and cocaine sensitization. Supporting this interpretation, we found that many genes impacted by NVHL or cocaine-Hx are associated with neurological disease, cell to cell signaling and interaction, and cell morphology.

The rarity of convergence of NVHL and cocaine-HX effects on individual genes, suggests that the NVHL model and cocaine-Hx interact on the neural network level as a composite orchestration of multiple genes and brain regions, rather than being reducible to one or a few molecular interactions. The lack of convergent, same direction effects of NVHL and cocaine-Hx on the same genes even though these interventions drive behavior in the same direction, is reminiscent of findings by Andrus et al, where two different rodent models of depression (genetic/inbred vs. environmental/ stress-exposure) impact mutually exclusive gene sets in amygdala and hippocampus(Andrus et al. 2012). As in Andrus et al, it is not clear which genes of interest we identified are central to the addiction vulnerability phenotypes or mental illness we are modeling. It is encouraging, however, that many genes altered by NVHL or cocaine-Hx showed expression levels that correlated with behavioral phenotypes (Table 2). Also, the enrichment of genes impacted by NVHL and cocaine-Hx (P < 0.01) among those varying most significantly according to litter of origin (Fig. 3a), suggests these disease models heuristically target genes showing strong natural variation in expression due to genetic and early-rearing environmental conditions.

Among genes most significantly regulated by NVHL or cocaine-Hx (Table 2), Esr2, Gfap, Cd40 and Dnajb1 were identified by Ingenuity as being associated with neuropsychiatric conditions including psychosis, bipolar disorder, major depression, Parkinsonism, Huntington disease and encephalopathy. Our own literature search identified additional functional associations linked to nine genes impacted by NVHL or cocaine-Hx, listed as follows: In the MPFC, Ptk2, upregulated by cocaine-Hx, undergoes normal prefrontal cortical upregulation through human adolescence(Choi et al. 2009), but pathological upregulation in human cocaine users(Lehrmann et al. 2003). Gfap (down by cocaine-Hx), shows expression deficits in the Wistar-Kyoto inbred rat model of depression (Gosselin et al. 2009). Zfhx2 (down by NVHL) has been KO'd in mice to produce depressive and hyperactive behavior (Komine et al. 2009), and is also downregulated in normal human peri-adolescent cortical development (Choi et al. 2009). Hydin, (up by NVHL) is associated with congenital hydrocephalus and microcephaly (Brunetti-Pierri et al. 2008) which in turn may serve as infantile risk factors for adult schizophrenia (Mcneil et al. 1993). In the NAC, Cxcl9 (down by NVHL) is associated with CNS injury and inflammation (Muller et al. 2010), while Krt23 (down by NVHL) is linked with epigenetic regulation of DNA expression, cellular cytoskeleton filaments and depression (Spijker et al. 2010; Zhang et al. 2001). Gpr177 and Psma5 (both up by NVHL) are respectively associated with Mu opiate receptor-regulation of dendritic atrophy and neurogenesis (Jin et al. 2010) vs. substantia nigra expression changes in Parkinson's disease (Grunblatt et al. 2004). Finally, in the CAPU, Slitrk3 (down by cocaine-Hx) is a neurotropin receptor protein upregulated in CNS neoplasms(Aruga et al. 2003). Notably, six of these nine genes (Ptk2, Zfhx2, Psma5, Gpr177, Krt23, Cxcl9) showed expression levels that correlated significantly with behavioral sensitization.

From among the few rat studies examining gene expression many days after cocaine dosing (Freeman et al. 2002, 2010; Toda et al. 2002; Yuferov et al. 2005) only one gene, Gfap, was identified as significant in our experiment. Lack of convergence among studies may be attributed to heterogeneity in cDNA/microarrays, statistical approaches, criteria for genes of interest, and dosing differences. Prior studies (Freeman et al. 2010; Yuferov et al. 2005) are consistent with our own in suggesting that gene expression changes due to a temporally distant cocaine history are hard to detect. Although a sensitizing cocaine history and NVHLs can both induce enduring changes in Delta-FosB protein levels in striatal circuits (Nestler et al. 2001; Powell et al. 2006), our study did not find alterations in fosb gene expression for either NVHL or Cocaine-Hx. This is explainable by the fact that we assessed mRNA and not protein; long lasting FosB protein elevations appear to linger after cocaine due to slow degradation rather than due to sustained elevations in RNA (Damez-Werno et al. 2012; Nestler et al. 2001).

In the only other examination of polygene expression in NVHL rats (using custom arrays including 5000 rat and 25 000 human cDNAs), which examined frontal-temporal cortices in F344 and Lewis strains, no genes of interest were identified in common with our own NVHL effects in the MPFC (Wong et al. 2005). An innovation of the present study beyond these prior studies is the application of an objectively measureable phenotypic behavior, cocaine behavioral sensitization, in addition to the mental illness/drug exposure models to delimit genes of interest. Over a third of the 75 named genes impacted by NVHL or cocaine-Hx, had expression levels that correlated significantly with behavioral sensitization (Table 2). In turn, 78% of these were altered by NVHL or cocaine-Hx in the same direction of change and in the same regions where NVHLs and cocaine-Hx have previously been shown to change neural network activation patterns produced by cocaine sensitization (Chambers et al. 2010a). Although we did identify two genes (Ptk2, Zfhx2) impacted by NVHL that also show peri-adolescent expression changes in human frontal cortex (Choi et al. 2009), it is not known whether genes impacted by NVHL show peri-adolescent emergence of expression abnormalities, or whether the NVHL preferentially impacts genes that show peri-adolescent expression changes in healthy rats. To our knowledge, no systematic studies of developmental changes in gene-expression in cortical–striatal circuits in Sprague-Dawley rats have been reported thus far. In mice, most post-natal developmental cortical gene expression changes occur as down regulations well before adolescence with changes starting during adolescence being very rare (Semeralul et al. 2006). Given the peri-adolescent onset of both the schizophrenia-like features of the NVHL model and addiction vulnerability present in animals and humans (Chambers et al. 2003), future studies are needed to determine how genes impacted by NVHL and cocaine-Hx are involved in peri-adolescent brain remodeling.

In conclusion, our findings suggest that a plurality of gene changes spanning neural networks that control decision making and motivated behavior may occur in mental illness to amplify addiction vulnerability. Future studies are needed to characterize how background genotype or environmental conditions may interact with NVHL-induced gene expression changes within cortical–striatal circuits. Similarly, more work in animals and humans is needed to elucidate how many molecular alterations happening in combination—that contribute to pathological neuronal signaling and morphology—co-conspire on the levels of information processing and learning and memory to generate addiction vulnerability in mental illness.

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  2. Abstract
  3. Materials and methods
  4. Results
  5. Discussion
  6. References
  7. Acknowledgements
  8. Supporting Information
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Acknowledgements

  1. Top of page
  2. Abstract
  3. Materials and methods
  4. Results
  5. Discussion
  6. References
  7. Acknowledgements
  8. Supporting Information

This research was funded by NIDA (K08) DA019850 (RAC) with support from the Indiana 21st Century Research and Technology Fund (HJE) and the Indiana Genomics Initiative. The Authors have no conflicts of interest to report.

Supporting Information

  1. Top of page
  2. Abstract
  3. Materials and methods
  4. Results
  5. Discussion
  6. References
  7. Acknowledgements
  8. Supporting Information
FilenameFormatSizeDescription
gbb12051-sup-0001-Tables1.docxWord 2007 document15KTable S1: (a) Experimental treatment group composition; (b) Number of probesets analyzed per region; (c) False Discovery Rates.
gbb12051-sup-0002-Tables2.docxWord 2007 document233KTable S2: Genes impacted by NVHL and cocaine-Hx main effects and interactions at P < 0.01.

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