Abstract
The cadherin 13 (CDH13) gene encodes a cell adhesion molecule likely to influence development and connections of brain circuits that modulate addiction, locomotion and cognition, including those that involve midbrain dopamine neurons. Human CDH13 mRNA expression differs by more than 80% in postmortem cerebral cortical samples from individuals with different CDH13 genotypes, supporting examination of mice with altered CDH13 expression as models for common human variation at this locus. Constitutive CDH13 knockout mice display evidence for changed cocaine reward: shifted dose response relationship in tests of cocaine-conditioned place preference using doses that do not alter cocaine-conditioned taste aversion. Reduced adult CDH13 expression in conditional knockouts also alters cocaine reward in ways that correlate with individual differences in cortical CDH13 mRNA levels. In control and comparison behavioral assessments, knockout mice display modestly quicker acquisition of rotarod and water maze tasks, with a trend toward faster acquisition of 5-choice serial reaction time tasks that otherwise displayed no genotype-related differences. They display significant differences in locomotion in some settings, with larger effects in males. In assessments of brain changes that might contribute to these behavioral differences, there are selective alterations of dopamine levels, dopamine/metabolite ratios, dopaminergic fiber densities and mRNA encoding the activity dependent transcription factor npas4 in cerebral cortex of knockout mice. These novel data and previously reported human associations of CDH13 variants with addiction, individual differences in responses to stimulant administration and attention deficit hyperactivity disorder (ADHD) phenotypes suggest that levels of CDH13 expression, through mechanisms likely to include effects on mesocortical dopamine, influence stimulant reward and may contribute modestly to cognitive and locomotor phenotypes relevant to ADHD.
INTRODUCTION
Cadherin 13 (CDH13) encodes a glycosylphosphatidyl inositol-anchored cell adhesion molecule whose variation is likely to alter connections between neurons in which it is expressed (1,2). CDH13 mRNA is prominently expressed by ventral tegmental area and substantia nigra pars compacta neurons that are implicated in reward, locomotor control and cognitive modulation (3,4). This localization increases interest in effects of CDH13 variation on dopaminergic brain systems and dopamine-associated behaviors.
Experiments that test the consequences of modifying CDH13 expression are also motivated by human molecular genetic studies. For addiction vulnerability and attention deficit hyperactivity disorder (ADHD), the CDH13 locus is marked by groups of clustered, nearby single nucleatide polymorphisms (SNPs) that display associations with 10−2 > p > 10−8 statistical significance in numerous independent case versus control genome wide association (GWAS) studies (5–15). CDH13 associations with the numbers of cigarettes smoked per day, reward reported after oral modest amphetamine doses and effects of individuals’ first five uses of alcohol are also described (7,16,17).
PubMed searches for cadherin 13 identify nine publications relating to normal brain, most of which relate to abovementioned CDH13 associations with substance dependence or ADHD. Two reports describe different CDH13 knockout mice, one with altered hippocampal function and modest influences on freezing and reversal learning during fear conditioning and Barnes maze tests (19,20). We now report the correlation of human CDH13 genotypes with individual differences in levels of CDH13 mRNAs in postmortem cerebral cortical samples. This finding, and failure to identify common disease-associated missense CDH13 variants, indicate that altered levels of CDH13 expression may represent a major genetic contribution to human interindividual differences at this locus. These human results help to motivate a variety of studies in mice with altered CDH13 expression.
In this paper, we study mice with constitutively altered and with adult (via conditional knockout) reductions in levels of CDH13 mRNA. We test these mice using conditioned place preference (CPP), a model of rewarding influences from drugs that has been highly validated in pharmacologic studies (18). Results support influences of CDH13 variation on addiction-related phenotypes and the possibility that drugs that modify activities of CDH13 might be useful when given to adults. Conclusions from CPP tests are buttressed by results of evaluations of other phenotypes, including tests of motor abilities (reductions might confound CPP results), learning/ memory (reductions might confound CPP results), aversive features caused by cocaine (which might provide an alternative explanation for CPP results to “altered reward”), impulsivity (which might fit with ADHD influences but confound CPP results) and anxiety (which might confound CPP results). We do report more subtle influences of CDH13 knockout on ADHD-related tests of locomotion in male mice and on performance during early acquisition trials for complex tasks.
When we test levels of monoamines in brains of the knockout mice as possible contributors to observed behavioral differences, we identify selectively altered cerebral cortical dopamine/ metabolite ratios and differences in dopaminergic fiber densities. These novel data, and recent work by others, provide substantial a posteriori likelihood that common human CDH13 “level of expression” variation contributes to differences in brain connections that are reflected in phenotypes relevant to addiction, stimulant actions, locomotor control and learning of complex tasks.
MATERIALS AND METHODS
Human brain samples for studies of CDH13 mRNAs in individuals with different CDH13 SNP alleles were obtained under protocols overseen by the Johns Hopkins (19% of samples) and University of Maryland (81% of samples) Institutional Review Boards. Mouse breeding and all experiments were performed under protocols approved by the NIDA-IRP Institutional Animal Care and Use Committee that complied with the Guide for the Care and Use of Laboratory Animals (8th edition, NRC 2011).
Human CDH13 mRNA correlation with CDH13 genomic markers was sought in frontal cortical autopsy samples (Johns Hopkins and University of Maryland brain banks) from European American individuals who lacked gross neuropathology. We focused on this genetic background and this brain region since this focus allow us to assemble a large a group of brain samples not possible using material from other brain regions or individuals with different racial/ethnic backgrounds. Most common causes of death were accidents/multiple trauma, cardiovascular disease and pulmonary embolisms. Average time to freezing was14 h. Brains came from individuals who were 50.5% female and with an average age 42. RNAs were prepared with the RNeasy lipid tissue mini kits (Qiagen), cDNA synthesized with SuperScript III first strand synthesis supermix (Invitrogen) and levels of mRNAs assessed by quantitative real-time polymerase chain reaction (RT-PCR) using SybrGreen master mix (Applied Biosystems) according to the manufacturer’s protocol using oligonucleotide primers (sequences available from authors on request) that targeted the dominant long CDH13 mRNA isoform 1 (www.ncbi.nlm.nih.gov/IEB/Research/Acembly) and the reference genes glyceraldehyde-3-phosphate dehydrogenase (GAPDH), hypoxanthine phosphoribosyltransferase 1 (HPRT1) and ubiquitin C (UBC).
CDH13 SNP genotyping was performed in DNA extracted from brain samples using Qiagen kits genotyped in multiplexed Sequenom panels (see Supplementary Materials).
Constitutive CDH13 knockout mice were produced by standard methods using embryonic stem cells from 129/sv mice and backcrossed for more than 15 generations to C57BL/6J mice (19). Mice from heterozygote × heterozygote matings were genotyped as described (19) and tested at 90 ± 43 d of age.
Conditional CDH13 knockout mice. CDH13loxP mice were produced as described (20) and bred with UBC-Cre/ERT2 mice (Jackson Laboratory; #008085) to obtain homozygous CDH13loxP/loxP; UBC-Cre/ERT2 ± and CDH13loxP/loxP; UBC-Cre/ERT2-/- mice.
CDH13 deletion was induced by treating adult mice (average 89-d-old) with tamoxifen (Sigma; 200 mg/kg/day intraperitoneal (i.p.)) for five days approximately two weeks prior to testing.
Cocaine-conditioned place preference was assessed as described (21,22). Briefly, preferences for one side of the apparatus were assessed, four 20 min conditioning trials conducted (two cocaine, two saline) and preferences were assessed again 24 h after the last conditioning session. Differences between times spent on the drug-paired side during the post- versus pre-tests were noted.
Cocaine-conditioned taste aversion consisted of habituation, conditioning and two-bottle testing, as described (23). After acclimation, handling and 20 min/d access to water, mice were given four series of 20-min conditioning sessions during which they were provided access to 1 g/L saccharin solution, then injected within 20 min with 0, 5, 10 or 20 mg/kg cocaine i.p., then 2 d of water recovery. Saccharin solution consumed when mice were given access to both saccharin and water for 20 min in a two-bottle-conditioned taste avoidance test was assessed.
Locomotion was recorded for 60 min in 42 × 42 cm dark, sound-attenuated boxes to which the mice had not been previously exposed and during conditioned place preference sessions of 20 min pretest (access to both halves of the 20 × 40 conditioning apparatus), conditioning (access to only 20 × 20 cm half of the apparatus) and test (access to 20 × 40 cm) sessions. Distances traveled were calculated from infrared beam breaks (Optovarimax ATS System) (22).
Motor coordination and learning were tested once per day over three consecutive days on a rotarod that accelerated from 4 to 40 rpm over 5 min.
Memory and learning were evaluated in a Morris water maze (24). A black 90-cm diameter pool filled with opaque 22°C water contained a 9-cm platform in the center of one quadrant that was visible for the first six trials and hidden 0.5 cm below the water level for subsequent trials. Mice received two trials, each lasting a maximum of 60 s, separated by a 15 s rest period on the platform. They were returned to home cages for 4 h, then given an additional 2-trial session. After acquisition, defined by an average latency to reach the platform of less than 10 s, the platform was removed and a 60 s probe trial conducted. Probe trial data including the path of the subject in the pool and the time spent in each quadrant were analyzed with Ethovision software (Noldus). After probe trials, the platform was placed in the opposite quadrant to assess reversal learning using the same procedure.
Five choice serial reaction time/learning was tested in light-proof, ventilated sound attenuated operant chambers (MED-NP5L; Med-Associates) with masking white noise, five wall holes that could be illuminated and an opposite-wall food tray that received 45-mg food pellets. Mice initially received a pellet if they poked the appropriate hole during the 60-s period during which it was illuminated (FR1 schedule). Any response during the response period ended the trial, which was followed by a 5-s intertrial interval. The 60-s stimulus duration used for the first block of trials was decreased to 30, 15, 7.5 and 4 s in successive weekly blocks of trials. Sessions ended after 50 food presentations or 40 min.
Anxiety was evaluated by testing time for emergence from a dark box (18 × 18 cm) through a 5-cm opening into a brightly illuminated 18 × 18 cm field, and thigmotaxis, time spent in near walls versus near the center of the 42 × 42 cm open field apparatus under red light conditions.
Monoamine/metabolite levels were examined in extracts of ventral midbrain, hippocampus, striatum and cerebral cortical specimens that were dissected on ice, frozen and stored at –80°C. Tissue samples were weighed, homogenized in 4°C 0.1 N HClO4 and concentrations of dopamine (DA), serotonin (5-HT) and their respective metabolites: 3,4- dihydroxyphenylacetic acid (DOPAC), homovanillic acid (HVA) and 5-hydroxyindoleacetic acid (5-HIAA) quantified using high-pressure liquid chromatography with a C18 column, mobile phase 50 mmol/L sodium phosphate monobasic, 250 M Na2 ethylenediamine tetraacetic acid (EDTA), 0.03% sodium octanesulfonic acid/25% methanol (final pH 2.75), Coulochem III detector (Thermo Scientific Dionex) and Empower 2 software Waters Corp.) as described (25). Peak heights of unknowns were compared to those of standards; lower limits of detection were 1 pg/20 μL.
Cortical dopamine fiber densities were examined in 50-μm coronal vibratome sections cut through six levels of frontal cortices (bregma +1.38 to +0.68 mm) of pentobarbital-anesthetized mice perfused through their left ventricles with 4% depolymerized paraformaldehyde in phosphate-buffered saline (PBS). Brains were postfixed for 4 h at 4°C, sectioned, and sections washed 3 times for 10 min in Tris buffered saline (TBS), then for 1 h at 4°C in TBS/3% normal donkey serum/0.1% Triton, incubated overnight at 4°C with rat antibodies recognizing dopamine transporter N-terminal sequences (MAB369, Millipore) diluted 1:1,000 in TBS/1% normal donkey serum/0.1% Triton, washed three times for 10 min in TBS, incubated for 2 h at 22°C with Alexa Fluora 488-conjugated donkey anti-rat IgG (A-21208, Life Technologies) diluted 1:2,400 in TBS/1% normal donkey serum/0.1% Triton, washed 3 times for 10 min in TBS and mounted onto slides using Prolong Gold (P-36931, Life Technologies). Tiled confocal immunofluorescence projection images from 11-level z stack images (1 μm total) were produced from each section using a Zeiss 710 microscope (40× objective, excitation 488 and emission 519 nm). The number of pixels that were members of groups of at least 100 contiguous pixels in which dopamine transporter (DAT) immunofluorescence was greater than two standard deviations above the mean value for each section was quantitated using ImageJ (version 1.48, NIH) by an observer unaware of genotype.
Mouse mRNAs were prepared and quantitated as noted for the human specimens from regional brain samples rapidly dissected from mouse brains. Expression of CDH13 mRNA in conditional knockouts was examined one week after CPP testing using oligonucleotides flCDH13f - flCDH13r anchored in the exon framed by the loxP sequences (exon 3) and CDH13af - CDH13ar, anchored in exons 7 and 8 (sequences available on request). Levels of mRNA corresponding to most mouse genes were compared using Affymetrix mouse gene 2.0 ST arrays, reagents recommended by the manufacturer (http://www.affymetrix.com/estore/catalog/131477/AFFY/Mouse+Genome+430+2.0+ Array#1_3), a 3000 7G scanner and software AGCC v3.0, expression console v1.3 and transcriptome analysis v2.0.
Statistical analyses from mouse behavioral data used analyses of covariance (ANCOVA) with “PASW” statistics 18 (SPSS). We use age as a cofactor and genotype, dose and gender as between subjects factors and report influences of age and gender as well as interactions, below which they reach significance. Secondary analyses used Scheffe’s post hoc and Student t tests (Excel). Saccharin preferences were analyzed using factorial ANOVA with between-subjects factors of genotype, sex and cocaine dose. Neurochemical data were expressed as pg/mg wet weight, including data for monoamines, metabolites and metabolite-to-parent ratios: [DOPC+HVA]/dopamine and 5-HIAA/5-HT. Data were analyzed using two-way ANOVA (genotype and sex). Averaged densities of dopamine transporter immunoreactive elements in projected images of six sections from five mice of each genotype were compared using t tests. Mouse expression array data was analyzed for triplicate arrays for each sample, three samples per genotype, using Gene Chip Operating Software v1.1.1 and a threshold of > two-fold difference in expression. Correlations between SNP genotypes and levels of expression in human postmortem samples used the association analysis toolset PLINK (26). Bonferroni corrections for multiple testing with observed, average 0.4 correlations (r) between CDH13 SNPs tested were performed using software available at (http://www.quantitativeskills.com/sisa/calculations /bonfer.php).
All supplementary materials are available online at www.molmed.org
RESULTS
We report results from mice with constitutively altered and with adult (via conditional knockout) reductions in levels of CDH13 mRNA. We test these mice using CPP, a model of rewarding influences from drugs that has been highly validated in pharmacological studies (18) and supported by results of several molecular genetic studies (see below). We identify evidence for shifted dose response relationships for cocaine reward in constitutive CDH13 knockouts and in mice with reduced adult expression. These data fit with human observations that support influences of CDH13 variation on addiction-related phenotypes, and with the idea that drugs that modify activities of CDH13, might be useful when given to adults.
We contrast these data with results of evaluations of other phenotypes that are of interest for several reasons. These include tests of motor abilities (reductions might confound CPP results), learning/memory (reductions might confound CPP results), aversive features caused by cocaine (which might provide an alternative explanation for CPP results to “altered reward”), impulsivity (which might fit with ADHD influences but confound CPP results) and anxiety (which might confound CPP results). Results of these tests identify no obvious alternative or confounding behavioral explanation for these CPP differences. We report more subtle influences of CDH13 knockout on ADHD-related tests of locomotion in male mice and on performance during early acquisition trials for complex tasks.
We test levels of monoamines in brains of the knockout mice as one possible contributor to the observed behavioral differences, and also test mRNA expression differences. In CDH13 cerebral cortices, we find selectively altered dopamine/metabolite ratios, differences in dopaminergic fiber densities and changes in an activity-dependent transcription factor mRNA. Each of these observations fits with CDH13 expression by dopaminergic neurons and subsets of cerebral cortical neurons and with contributions of changed dopaminergic innervation to the observed behavioral data.
Human CDH13 Variation Versus Expression Levels
CDH13 mRNA was detected in RNA extracted from cerebral cortical specimens from each of 184 individuals. There was good (r > 0.85) agreement between results obtained with amplimers targeting different parts of this mRNA. Levels of CDH13 expression were significantly associated with allele frequencies for SNPs in CDH13 intron 2 (Table S4). Nearby intron 2 SNPs, rs8059696, rs4783277, rs12596958 and rs2199430, displayed minor allele frequencies ca 0.35, span about 8 kb and displayed nominally significant, 0.045 > p > 0.001 association with levels of CDH13 expression. Brains from individuals with rs2199430 = GG displayed 181% of the mean levels of CDH13 mRNA found in AA homozygotes (Supplementary Figure S1; p = 0.0007 ANOVA; Bonferroni-corrected threshold p = 0.003).
Mouse CDH13 Expression
Heterozygote constitutive knockouts expressed approximately 50% of the wild-type levels of CDH13 mRNA. Homozygote knockouts did not express detectable levels of this RNA (Supplement, Supplementary Figure S2A). Individual conditional knockouts sacrificed following CPP testing revealed varying levels of cerebral cortical expression of CDH13 mRNA (Supplementary Figure S2B; see below).
Cocaine CPP in Constitutive CDH13 Knockout Mice
Knockouts displayed altered dose/response relationships for cocaine CPP (Figure 1A, p = 0.002 for genotypeBdose interaction, ANCOVA with age as covariate). In wild-type mice, 5, 10 and 20 mg/kg doses of cocaine induced significant place preferences (Scheffe’s p = 0.035, < 0.001 and < 0.001, respectively). In wild-type animals, significantly more robust preference was produced by 10 than by 5 mg/kg doses (p = 0.006). By contrast, homozygous CDH13 knockout mice displayed significant preferences only for places paired with 5 mg/kg cocaine (p = 0.002). Preferences induced by pairing with 10 or 20 mg/kg doses did not differ significantly from values in control, saline-injected animals (p = 0. 38 and 0.10). Heterozygous mice provided intermediate preferences for the places paired with 5, 10 and 20 mg/kg cocaine doses that achieved statistical significance (Scheffe’s p = 0.006, 0.029 and 0.007). Mice with reduced CDH13 expression thus display reduced reward from a normally highly rewarding 10 mg/kg cocaine dose (ANOVA p = 0.012). They also display even more significant increases in preference for places paired with the 5 mg/kg dose (ANOVA p = 0.003). These data suggest a leftward shift of the initial limb of the inverted U dose- response relationship typically noted for cocaine reward and reinforcement. Dose–response relationships were similar in male and female mice (ANCOVA sexBgenotypeBdose, p = 0.633).
Cocaine CPP in Conditional CDH13 Knockout Mice
Mice in which expression was reduced in adulthood also increased preference for places paired with modest doses of cocaine (Figure 1B, ANCOVA genotypeBdose, p = 0.017; n = 11–12/group). Cre expressing mice showed significantly stronger preferences for places paired with 4 mg/kg cocaine than the control Cre-/- mice (p = 0.018). There was a r = –0.42; one-tailed p = 0.035 correlation between preference for the place paired with this modest cocaine dose and levels of CDH13 mRNAs assessed in cortices of mice sacrificed following the conditioned place preference testing (Supplementary Figure S2B).
Cocaine-Conditioned Taste Aversion
There were no significant influences of genotype on acquisition of the taste aversion. In two-bottle tests (Figure 1C), there were significant effects of genotype and dose (p = 0.029 and 0.009, respectively) but no significant genotypeBdose interaction (p = 0.30). Conditioning with 20 mg/kg of cocaine significantly reduced saccharin preference in mice of all genotypes (p = 0.006).
Locomotion
During the first exposure to the 49 × 49 cm arena, ANCOVA identified a p = 0.023 effect of genotype on locomotion. Genotype effects were significant when data from males were analyzed separately (Supplementary Figure S3A, p = 0.034) but not when data from females was analyzed separately (Supplementary Figure S3B, p = 0.265).
During the first preconditioning session in the CPP apparatus (Supplementary Figure S4A), there was a significant genotypeBage interaction (ANCOVA, p = 0.045). Constitutive CDH13 knockout mice older than 90 d displayed less locomotion than their wild type siblings (ANOVA, p = 0.018). In mice <90 d old, genotype effects on locomotion did not reach significance (ANOVA, p = 0.095). There was no significant effect of genotype on locomotion monitored when mice were confined to halves of the conditioned place preference apparatus after treatments with saline, 5, 10 or 20 mg/kg cocaine doses (Supplementary Figure S4B; ANCOVA, p = 0.15, 0.13 and 0.09, respectively; ANCOVA overall effect of genotype, p = 0.31, genotypeBdose interaction, p = 0.88).
Rotarod Testing
Knockout mice displayed a significant overall influence of genotype on the arc of learning this task (repeated measures ANCOVA day of testBgenotype interaction, p = 0.040) (Figure 2A). This influence was greatest during the second test day (ANVOVA, effect of genotype, p = 0.017), when knockouts performed better than wild-type littermates.
Morris Water Maze
Knockout mice displayed no significant deficit in Morris water maze tests of acquisition (Figure 2B; repeated measures ANCOVA genotypeBday, p = 0. 96), reversal learning (repeated measures ANCOVA genotypeBday, p = 0. 81), the first probe trial (Supplementary Figure S5B; including distance from the former platform location ANOVA, p = 0.13; time spent searching in the target quadrant p = 0.12; time spent searching in the opposite quadrant, p = 0.32; and swimming speed, p = 0.45) or the second probe trial after the platform had been moved to a new location. On the contrary, there was modest support for more rapid acquisition of the task in the knockouts, when compared to mice of both other genotypes (Figure 2B, p = 0.039; t test).
Five choice serial reaction time: Knockout mice displayed no significant deficit in 5-choice serial reaction time testing (Figure 2C, Supplementary Figure S6). During the first and second days of sessions in this apparatus, knockout male mice displayed 35 and 54% correct responses, while their wild-type littermates displayed 37 and 42% correct (Figure 2C), though these differences failed to achieve statistical significance (p = 0.1). Knockout mice made no more premature responses or omission errors than wild-type littermates (Supplementary Figure S6).
Anxiety
CDH13KO mice did not differ from their wild-type siblings in latencies to emerge from a dark compartment or time spent in the light (Supplementary Figure S7A; ANCOVA effect of genotype, p = 0.2). There were no significant differences in the amount of time that they spent in the center of an open field (Supplementary Figure S7B; ANCOVA effect of genotype, p = 0.75).
Mouse Brain Neurochemistry
In cortex, levels of dopamine were significantly reduced in constitutive CDH13 knockout mice (Figure 3A; ANOVA, p = 0.006). Ratios between dopamine and its metabolites also differed significantly (Figure 3D; ANOVA, p = 0.007). However, there were no significant differences in levels of dopamine, HVA or DOPAC in striatum, ventral midbrain or hippocampus (Figures 3B, C). There were no significant genotype-related differences in levels of norepinephrine, serotonin or its metabolite 5HIAA in cortex, striatum, hippocampus or ventral midbrain.
Cortical Dopamine Transporter (DAT) Immunohistochemistry
Infralimbic and frontal cortical regions displayed densities of DAT-immunoreactive elements in fiber/varicosity patterns that were indistinguishable from those reported using several anti-DAT sera and material from several species (27,28). Knockout mice displayed 1.3× the density of dopamine transporter immunoreactivity displayed by wild-type littermates (p = 0.005, t test; Figures 3E, F).
DISCUSSION
CDH13 is a cell adhesion molecule expressed by neurons in brain circuits that include ventral midbrain substantia nigra and ventral tegmental area neurons, likely dopaminergic, whose activities are modulated by virtually every abused substance and by most ADHD pharmacotherapeutics (29–31). Homotypic interactions between CDH13 molecules on adjacent surfaces of expressing neurons are likely to alter the ways in which dopaminergic and other brain circuits that are implicated in addiction and motor modulation develop and are modified by pharmacological and physiological challenges (1,32–34).
The evidence for cis-regulation of CDH13 expression in humans identified in the current work adds to the posterior probabilities that CDH13 variation does alter addiction and ADHD-related phenotypes. The robust, ca. 80% differences in cerebral cortical expression of CDH13 mRNA that we identify between individuals with common 5’ CDH13 genotypes provides a link between data from the knockouts and common human allelic functional variation at this gene locus. SNPs in this 8 kb CDH13 intron 2 genomic region display nominally significant associations with addiction-related phenotypes; 9 of 17 and 8 of 20 tested SNPs display 0.05 > p > 2 × 10−6 pmin associations with abilities to quit smoking or dependence on an addictive substance, repsectively (36). The intron 2 CDH13 SNP that displays the strongest association with level of CDH13 mRNA expression lies within 2 kb of a cluster of CDH13 SNPs that display the strongest associations with human temporal lobe volume (35). Mutually supporting positive and negative human and mouse data thus suggest that common CDH13 alleles that alter levels of expression in ways that provide links between individual differences identified in humans and differences that we report here in mouse models.
Characterization of mice with lifelong alterations in CDH13 expression supports a pattern of specific behavioral changes. Constitutive CDH13 knockout mice display alterations in their preference for the places paired with several different doses of cocaine. There is no corresponding influence of reduced CDH13 expression on the aversive features provided by these same cocaine doses, as assessed by conditioned taste aversion (36). There is no evidence for differences in anxiety phenotypes, which might otherwise interact with CPP testing (37). Constitutive knockout mice fail to display sizable alterations in locomotion or strength likely to confound CPP testing (38,39).
Effects on preference for places paired with a modest cocaine dose were also observed in conditional knockouts in which expression of CDH13 was changed only in adulthood. Developmental alterations in circuitry thus do not appear to be required to provide these most significant effects of altered CDH13 expression. We focused on influences of 4 mg/kg doses since these provided the largest differences in initial studies of these conditional knockouts. The significant correlations between mouse-to-mouse differences in levels of cortical CDH13 mRNA and preferences for places paired with 4 mg/kg doses do provide evidence for a graded relationship between levels of adult CDH13 expression and preference for this modest cocaine dose. It is conceivable that effects on reward from larger (e.g., 10 mg/kg) cocaine doses might require lifelong reductions in CDH13 expression levels, however.
Subtle knockout influences on locomotion and cognitive performances reach significance in several interesting ways. Knockouts overall, and males analyzed separately, display significant differences in locomotion in a larger dark chamber. Knockouts of both genders display better performance during their second exposures to rotarod and Morris water maze testing. Each of these observations fit with reported modest human CDH13 associations with ADHD, which is more frequently diagnosed in males (40). However, the sizes of these effects are small, as are the modest effects noted by others in some mnemonic parameters of the conditional knockout mice (20). There are also no effects of constitutive changes in CDH13 on trained performance on the 5-choice serial reaction time task; the same result came from conditional CDH13 knockouts (20). The impulsivity phenotype assessed by this test (41) is thus not changed with CDH13 deletion.
Molecular, neurochemical and anatomic findings from CDH13 knockout mice provide evidence for specificity that complements behavioral results. Initial neurochemical studies highlighted specific changes in dopamine and its metabolites in cerebral cortex. These findings contrasted with lack of significant knockout versus wild-type differences in levels of other monoamines in any brain region sampled, or of dopamine in ventral midbrain or striatum. Neurochemical findings in cortex were then supported by changes in densities in dopamine-transporter immunoreactive fibers using a pixel based method; we obtained similar observations in initial studies using counts of labeled fibers by paired independent observers who were unaware of genotype. The greater fiber densities noted in knockouts and the elevated dopamine turnover (42) suggested by the altered ratios between dopamine and its major metabolites are each consistent with in vitro observations that CDH13-CDH13 interactions can inhibit outgrowth of CDH13-expressing neuronal processes (34). Microarray results that point to substantial changes in cortical expression of only the activity- dependent transcription factor Npas4 (43) comport with both subtly altered cortical circuitry in the CDH13 knockouts and with the substantial specificity of the changes that CDH13 deletion induces.
Evidence available prior to and following our CPP results also supports differences in dose response relationships for addictive substances in individuals with differences in CDH13 genotypes (44). Prior to these mouse results, there were reports of associations between CDH13 markers and smoking quantity/frequency (7) and dose-response relationships for symptoms of intoxication during individuals’ first five exposures to alcohol (45). After we had obtained the initial CPP data from constitutive knockouts, Hart and colleagues reported associations between CDH13 variants and human individual differences in the dose-response relationships for amphetamine effects (16). There was a robust CDH13 association with individual differences in subjective positive responses to oral administration of 10 mg, but not 20 mg amphetamine doses.
Evidence from mouse studies that CDH13 variation is associated with both cognitive and motor differences that could alter vulnerability to ADHD fits with human ADHD associations that were largely available as we performed the mouse experiments. The differences in locomotion that we identify here display interactions with gender that are reminiscent of the influences of gender on ADHD diagnoses and/or symptomatology. CDH13 associations with cognitive function in children with ADHD or autism fit nicely with the influences of CDH13 variation on task acquisition that we note here (46–48). We failed to identify any significant influences of CDH13 variation on the sorts of impulsivity measured by 5-choice serial reaction time testing (49), although this “impulsivity” indicator may not assess all forms of impulsivity present in human disorders. Nevertheless, CDH13 variation does appear to provide subtle influences on both cognitive and motor systems in ways that could (subtly) alter likelihood of obtaining an ADHD diagnosis in several ways.
Our observations of altered cerebral cortical dopamine/metabolite levels and ratios in the CDH13 knockouts provide a plausible neurochemical correlate for at least some of the specific influences of the knockout on drug reward. Homomeric recognition of CDH13 expressed by ventral tegmental area mesocortically projecting dopamine neurons and by many of the frontal cerebral cortical neurons that they target is likely to alter connections between these two important nodes of addiction-related circuitry.
Results from mice with altered CDH13 expression are reinforced by data from human associations that were available both prior to and following availability of the initial mouse CPP results. Prior probabilities for influences of CDH13 variation on addiction and ADHD phenotypes in mice were enhanced by findings, in several addiction and some ADHD association datasets, that clusters of nearby CDH13 SNPs display nominally significant 10−2 > p > 10−8 case versus control allele frequency differences (5,7,9,10,14,16,45,50–58). Cautions in interpreting this human data, taken alone, included the lack of large effects of any single CDH13 variant. Nevertheless, prior datasets, subsequent addiction-related studies and a meta-analysis of ADHD data (59) that do identify CDH13 supported elevated prior probabilities that CDH13 associations would be identified in the current work. In light of these prior probabilities, the robust influences of CDH13 knockout on stimulant-conditioned place preference and modest influences on motor/learning phenotypes that are consistent with ADHD associations elevate posterior probabilities that CDH13 variation does provide bona fide influences on addiction- and ADHD-related phenotypes.
CDH13 variation, implicated in addiction, in rewarding and/or aversive responses to stimulants and alcohol and in ADHD by human molecular genetic studies, provides a pattern of altered behaviors in a mouse model that accords remarkably with human data for these phenotypes. In future work, it will be interesting to see if mice with reduced CDH13 expression display differences in responses to natural rewards and/or reward from other substances of abuse. Nevertheless, the present results support the important roles that detailed patterns of neuronal connections (6), including those modulated by CDH13, are likely to play in addiction and other complex brain phenotypes. These data add to support for CDH13 as a candidate druggable target for therapies for addictions and/or ADHD (60).
CONCLUSION
Few of the likely polygenic influences on human vulnerabilities to addiction or attention deficit hyperactivity disorder (ADHD) have been elucidated in detail or in animal models. Mice with lifelong reductions in expression of cadherin 13 (CDH13) display sizable differences in tests of stimulant reward, modest/ gender-specific influences on locomotor behaviors (though not 5-choice testing) of possible relevance to ADHD and altered cortical dopamine systems that could contribute to these behavioral observations. Mouse and human data are linked by differences in CDH13 mRNA expression in brains of humans with different CDH13 genotypes and by human associations of CDH13 variants with addiction, stimulant reward and ADHD phenotypes. These data and altered cocaine reward in mice with adult reductions in CDH13 expression support CDH13 as a novel therapeutic target.
Supplementary Material
ACKNOWLEDGMENTS
We are grateful for help from C Johnson, D Arking, D Naimen, J Bader, M Morales and J Schroder, for access to CDH13 association data from A Hart, A Palmer, O Kohannim and P Thompson and for access to brain samples from the University of Maryland Brain Tissue Bank. Correspondence concerning CDH13 knockout mice to BR, at 10901 N. Torrey Pines Road, La Jolla, CA 92037.
Footnotes
Online address: http://www.molmed.org
DISCLOSURE
This work was supported by the National Institutes of Health (NIH)–Intramural Research Program, NIDA, DHHS and the Biomedical Research Institute of New Mexico (G Uhl), NIH grant HL102680 (B Ranscht), the European Community (EC: AGGRESSOTYPE FP7/No. 602805 (OR and KPL), the DFG (SFB TRR 58/A5 OR and KPL) and the Fritz Thyssen Foundation (Az.10.13.1185 OR and KPL).
Cite this article as: Drgonova J, et al. (2016) Cadherin 13: Human cis-regulation and selectively altered addiction phenotypes and cerebral cortical dopamine in knockout mice. Mol. Med. 22:537–47.
REFERENCES
- Ranscht B, Dours-Zimmermann MT. T-cadherin, a novel cadherin cell adhesion molecule in the nervous system lacks the conserved cytoplasmic region. Neuron. 1991;7:391–402. doi: 10.1016/0896-6273(91)90291-7. [DOI] [PubMed] [Google Scholar]
- Vestal DJ, Ranscht B. Glycosyl phosphatidylinositol—anchored T-cadherin mediates calcium-dependent, homophilic cell adhesion. J Cell Biol. 1992;119:451–61. doi: 10.1083/jcb.119.2.451. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Saddoris MP, Sugam JA, Cacciapaglia F, Carelli RM. Rapid dopamine dynamics in the accumbens core and shell: learning and action. Front Biosci (Elite Ed) 2013;5:273–88. doi: 10.2741/e615. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Lein ES, Hawrylycz MJ, Ao N, Ayres M, Bensinger A, Bernard A, et al. Genome-wide atlas of gene expression in the adult mouse brain. Nature. 2007;445:168–76. doi: 10.1038/nature05453. [DOI] [PubMed] [Google Scholar]
- Treutlein J, Cichon S, Ridinger M, Wodarz N, Soyka M, Zill P, et al. Genomewide association study of alcohol dependence. Arch Gen Psychiatry. 2009;66:773–84. doi: 10.1001/archgenpsychiatry.2009.83. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Uhl GR, Drgon T, Johnson C, Li CY, Contoreggi C, Hess J, et al. Molecular genetics of addiction and related heritable phenotypes: genome-wide association approaches identify “connectivity constellation” and drug target genes with pleiotropic effects. Ann N Y Acad Sci. 2008;1141:318–81. doi: 10.1196/annals.1441.018. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Thorgeirsson TE, Gudbjartsson DF, Surakka I, Vink JM, Amin N, Geller F, et al. Sequence variants at CHRNB3-CHRNA6 and CYP2A6 affect smoking behavior. Nat Genet. 2010;42:448–53. doi: 10.1038/ng.573. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Drgon T, Johnson CA, Nino M, Drgonova J, Walther DM, Uhl GR. “Replicated” genome wide association for dependence on illegal substances: genomic regions identified by overlapping clusters of nominally positive SNPs. American Journal of Medical Genetics Part B Neuropsychiatric Genetics. 2011;156:125–38. doi: 10.1002/ajmg.b.31143. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Uhl GR, Drgon T, Liu QR, Johnson C, Walther D, Komiyama T, et al. Genomewide association for methamphetamine dependence: convergent results from 2 samples. Arch Gen Psychiatry. 2008;65:345–55. doi: 10.1001/archpsyc.65.3.345. [DOI] [PubMed] [Google Scholar]
- Johnson C, Drgon T, Walther D, Uhl GR. Genomic regions identified by overlapping clusters of nominally-positive SNPs from genome-wide studies of alcohol and illegal substance dependence. PLoS One. 2011;6 doi: 10.1371/journal.pone.0019210. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Johnson C, Drgon T, Liu QR, Walther D, Edenberg H, Rice J, et al. Pooled association genome scanning for alcohol dependence using 104,268 SNPs: validation and use to identify alcoholism vulnerability loci in unrelated individuals from the collaborative study on the genetics of alcoholism. American Journal of Medical Genetics Part B Neuropsychiatric Genetics. 2006;141B:844–53. doi: 10.1002/ajmg.b.30346. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Liu QR, Drgon T, Johnson C, Walther D, Hess J, Uhl GR. Addiction molecular genetics: 639,401 SNP whole genome association identifies many “cell adhesion” genes. American Journal of Medical Genetics Part B Neuropsychiatric Genetics. 2006;141B:918–25. doi: 10.1002/ajmg.b.30436. [DOI] [PubMed] [Google Scholar]
- Johnson C, Drgon T, Liu QR, Zhang PW, Walther D, Li CY, et al. Genome wide association for substance dependence: convergent results from epidemiologic and research volunteer samples. BMC Med Genet. 2008;9 doi: 10.1186/1471-2350-9-113. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Drgon T, Montoya I, Johnson C, Liu QR, Walther D, Hamer D, et al. Genomewide association for nicotine dependence and smoking cessation success in NIH research volunteers. Mol Med. 2009;15:21–7. doi: 10.2119/molmed.2008.00096. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Uhl GR, Walther D, Musci R, Fisher C, Anthony JC, Storr CL, et al. Smoking quit success genotype score predicts quit success and distinct patterns of developmental involvement with common addictive substances. Mol Psychiatry. 2012 doi: 10.1038/mp.2012.155. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Hart AB, Engelhardt BE, Wardle MC, Sokoloff G, Stephens M, de Wit H, et al. Genome-wide association study of d-amphetamine response in healthy volunteers identifies putative associations including cadherin 13 (CDH13) PLoS One. 2012;7 doi: 10.1371/journal.pone.0042646. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Joslyn G, Ravindranathan A, Brush G, Schuckit M, White RL. Human variation in alcohol response is influenced by variation in neuronal signaling genes. Alcoholism Clinical and Experimental Research. 2010;34:800–12. doi: 10.1111/j.1530-0277.2010.01152.x. [DOI] [PubMed] [Google Scholar]
- Tzschentke TM. Measuring reward with the conditioned place preference paradigm: a comprehensive review of drug effects, recent progress and new issues. Prog Neurobiol. 1998;56:613–72. doi: 10.1016/s0301-0082(98)00060-4. [DOI] [PubMed] [Google Scholar]
- Hebbard LW, Garlatti M, Young LJ, Cardiff RD, Oshima RG, Ranscht B. Tcadherin supports angiogenesis and adiponectin association with the vasculature in a mouse mammary tumor model. Cancer Res. 2008;68:1407–16. doi: 10.1158/0008-5472.CAN-07-2953. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Rivero O, Selten MM, Sich S, Popp S, Bacmeister L, Amendola E, Negwer M, Schubert D, Proft F, Kiser D, Schmitt AG, Gross C, Kolk SM, Strekalova T, van den Hove D, Resink TJ, Nadif Kasri N, Lesch KP. Cadherin-13, a risk gene for ADHD and comorbid disorders, impacts GABAergic function in hippocampus and cognition. Transl Psychiatry. 2015;13:5–e655. doi: 10.1038/tp.2015.152. doi: 10.1038/tp.2015.152. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Drgonova J, Zimonjic DB, Hall FS, Uhl GR. Effect of KEPI (Ppp1r14c) deletion on morphine analgesia and tolerance in mice of different genetic backgrounds: when a knockout is near a relevant quantitative trait locus. Neuroscience. 2010;165:882–95. doi: 10.1016/j.neuroscience.2009.10.007. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Hall FS, Centeno M, Perona MT, Adair J, Dobner PR, Uhl GR. Effects of neurotensin gene knockout in mice on the behavioral effects of cocaine. Psychopharmacology (Berl) 2011 doi: 10.1007/s00213-011-2370-9. [DOI] [PubMed] [Google Scholar]
- Serafine KM, Riley AL. Possible role of norepinephrine in cocaine-induced conditioned taste aversions. Pharmacol Biochem Behav. 2009;92:111–16. doi: 10.1016/j.pbb.2008.10.019. [DOI] [PubMed] [Google Scholar]
- Morris R. Developments of a water-maze procedure for studying spatial learning in the rat. J Neurosci Methods. 1984;11:47–60. doi: 10.1016/0165-0270(84)90007-4. [DOI] [PubMed] [Google Scholar]
- Baumann MH, Ayestas MA, Jr, Partilla JS, Sink JR, Shulgin AT, Daley PF, et al. The designer methcathinone analogs mephedrone and methylone are substrates for monoamine transporters in brain tissue. Neuropsychopharmacology. 2012;37:1192–203. doi: 10.1038/npp.2011.304. [DOI] [PMC free article] [PubMed] [Google Scholar]
- (http://pngu.mgh.harvard.edu/~purcell/plink/)
- Freed C, Revay R, Vaughan RA, Kriek E, Grant S, Uhl GR, et al. Dopamine transporter immunoreactivity in rat brain. J Comp Neurol. 1995;359:340–49. doi: 10.1002/cne.903590211. [DOI] [PubMed] [Google Scholar]
- Sesack SR, Hawrylak VA, Guido MA, Levey AI. Cellular and subcellular localization of the dopamine transporter in rat cortex. Adv Pharmacol. 1998;42:171–4. doi: 10.1016/s1054-3589(08)60720-6. [DOI] [PubMed] [Google Scholar]
- Volkow ND, Wang GJ, Fowler JS, Tomasi D. Addiction circuitry in the human brain. Annu Rev Pharmacol Toxicol. 2012;52:321–36. doi: 10.1146/annurev-pharmtox-010611-134625. [DOI] [PMC free article] [PubMed] [Google Scholar]
- De Mei C, Ramos M, Iitaka C, Borrelli E. Getting specialized: presynaptic and postsynaptic dopamine D2 receptors. Curr Opin Pharmacol. 2009;9:53–8. doi: 10.1016/j.coph.2008.12.002. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Sinita E, Coghill D. The use of stimulant medications for non-core aspects of ADHD and in other disorders. Neuropharmacology. 2014 doi: 10.1016/j.neuropharm.2014.06.014. [DOI] [PubMed] [Google Scholar]
- Ranscht B. Cadherins: molecular codes for axon guidance and synapse formation. International Journal of Developmental Neuroscience. 2000;18:643–51. doi: 10.1016/s0736-5748(00)00030-7. [DOI] [PubMed] [Google Scholar]
- Philippova M, Joshi MB, Kyriakakis E, Pfaff D, Erne P, Resink TJ. A guide and guard: the many faces of T-cadherin. Cell Signal. 2009;21:1035–1044. doi: 10.1016/j.cellsig.2009.01.035. [DOI] [PubMed] [Google Scholar]
- Ciatto C, Bahna F, Zampieri N, VanSteenhouse HC, Katsamba PS, Ahlsen G, et al. T-cadherin structures reveal a novel adhesive binding mechanism. Nat Struct Mol Biol. 2010;17:339–47. doi: 10.1038/nsmb.1781. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Kohannim O, Hibar DP, Stein JL, Jahanshad N, Hua X, Rajagopalan P, et al. Discovery and Replication of Gene Influences on Brain Structure Using LASSO Regression. Front Neurosci. 2012;6 doi: 10.3389/fnins.2012.00115. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Verendeev A, Riley AL. The role of the aversive effects of drugs in selfadministration: assessing the balance of reward and aversion in drug-taking behavior. Behav Pharmacol. 2013;24:363–74. doi: 10.1097/FBP.0b013e32836413d5. [DOI] [PubMed] [Google Scholar]
- Dennis TS, Beck KD, Bobzean SA, Dougall AL, Perrotti LI. Assessing learned associations between conditioned cocaine reward and environmental stimuli in the Wistar Kyoto rat. Pharmacol Biochem Behav. 2012;103:76–82. doi: 10.1016/j.pbb.2012.08.005. [DOI] [PubMed] [Google Scholar]
- Tyrberg B, Miles P, Azizian KT, Denzel MS, Nieves ML, Monosov EZ, et al. Tcadherin (Cdh13) in association with pancreatic beta-cell granules contributes to second phase insulin secretion. Islets. 2011;3:327–37. doi: 10.4161/isl.3.6.17705. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Williams AS, Kasahara DI, Verbout NG, Fedulov AV, Zhu M, Si H, et al. Role of the adiponectin binding protein T-cadherin (Cdh13), in allergic airways responses in mice. PLoS One. 2012;7 doi: 10.1371/journal.pone.0041088. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Wittchen HU, Jacobi F, Rehm J, Gustavsson A, Svensson M, Jonsson B, et al. The size and burden of mental disorders and other disorders of the brain in Europe 2010. Eur Neuropsychopharmacol. 2011;21:655–79. doi: 10.1016/j.euroneuro.2011.07.018. [DOI] [PubMed] [Google Scholar]
- Uhl G. Premature poking: impulsivity, cocaine and dopamine. Nat Med. 2007;13:413–14. doi: 10.1038/nm0407-413. [DOI] [PubMed] [Google Scholar]
- Murotani T, Ishizuka T, Hattori S, Hashimoto R, Matsuzaki S, Yamatodani A. High dopamine turnover in the brains of Sandy mice. Neurosci Lett. 2007;421:47–51. doi: 10.1016/j.neulet.2007.05.019. [DOI] [PubMed] [Google Scholar]
- Benito E, Barco A. The Neuron al Activity-Driven Transcriptome. Mol Neurobiol. 2014 doi: 10.1007/s12035-014-8772-z. [DOI] [PubMed] [Google Scholar]
- Uhl GR, Drgonova J, Hall FS. Curious cases: Altered dose-response relationships in addiction genetics. Pharmacol Ther. 2014;141:335–46. doi: 10.1016/j.pharmthera.2013.10.013. [DOI] [PubMed] [Google Scholar]
- Joslyn G, Ravindranathan A, Brush G, Schuckit M, White RL. Human variation in alcohol response is influenced by variation in neuronal signaling genes. Alcohol Clin Exp Res. 2010;34:800–12. doi: 10.1111/j.1530-0277.2010.01152.x. [DOI] [PubMed] [Google Scholar]
- Arias-Vasquez A, Altink ME, Rommelse NN, Slaats-Willemse DI, Buschgens CJ, Fliers EA, et al. CDH13 is associated with working memory performance in attention deficit/hyperactivity disorder. Genes Brain Behav. 2011;10:844–51. doi: 10.1111/j.1601-183X.2011.00724.x. [DOI] [PubMed] [Google Scholar]
- Chapman NH, Estes A, Munson J, Bernier R, Webb SJ, Rothstein JH, et al. Genome-scan for IQ discrepancy in autism: evidence for loci on chromosomes 10 and 16. Hum Genet. 2011;129:59–70. doi: 10.1007/s00439-010-0899-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Wang K, Zhang H, Ma D, Bucan M, Glessner JT, Abrahams BS, et al. Common genetic variants on 5p14.1 associate with autism spectrum disorders. Nature. 2009;459:528–33. doi: 10.1038/nature07999. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Bari A, Robbins TW. Inhibition and impulsivity: behavioral and neural basis of response control. Prog Neurobiol. 2013;108:44–79. doi: 10.1016/j.pneurobio.2013.06.005. [DOI] [PubMed] [Google Scholar]
- Uhl GR, Liu QR, Drgon T, Johnson C, Walther D, Rose JE, et al. Molecular genetics of successful smoking cessation: convergent genome-wide association study results. Arch Gen Psychiatry. 2008;65:683–93. doi: 10.1001/archpsyc.65.6.683. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Uhl GR, Drgon T, Johnson C, Ramoni MF, Behm FM, Rose JE. Genome-wide association for smoking cessation success in a trial of precessation nicotine replacement. Mol Med. 2010;16:513–26. doi: 10.2119/molmed.2010.00052. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Drgon T, Johnson C, Walther D, Albino AP, Rose JE, Uhl GR. Genome-wide association for smoking cessation success: participants in a trial with adjunctive denicotinized cigarettes. Mol Med. 2009;15:268–74. doi: 10.2119/molmed.2009.00040. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Uhl GR, Drgon T, Johnson C, Walther D, David SP, Aveyard P, et al. Genomewide association for smoking cessation success: participants in the Patch in Practice trial of nicotine replacement. Pharmacogenomics. 2010;11:357–67. doi: 10.2217/pgs.09.156. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Johnson C, Drgon T, Liu QR, Walther D, Edenberg H, Rice J, et al. Pooled association genome scanning for alcohol dependence using 104,268 SNPs: validation and use to identify alcoholism vulnerability loci in unrelated individuals from the collaborative study on the genetics of alcoholism. Am J Med Genet B Neuropsychiatr Genet. 2006;141B:844–53. doi: 10.1002/ajmg.b.30346. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Drgon T, Johnson CA, Nino M, Drgonova J, Walther DM, Uhl GR. “Replicated” genome wide association for dependence on illegal substances: genomic regions identified by overlapping clusters of nominally positive SNPs. Am J Med Genet B Neuropsychiatr Genet. 2011;156:125–38. doi: 10.1002/ajmg.b.31143. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Liu QR, Drgon T, Johnson C, Walther D, Hess J, Uhl GR. Addiction molecular genetics: 639,401 SNP whole genome association identifies many “cell adhesion” genes. Am J Med Genet B Neuropsychiatr Genet. 2006;141B:918–25. doi: 10.1002/ajmg.b.30436. [DOI] [PubMed] [Google Scholar]
- Lasky-Su J, Neale BM, Franke B, Anney RJ, Zhou K, Maller JB, et al. Genomewide association scan of quantitative traits for attention deficit hyperactivity disorder identifies novel associations and confirms candidate gene associations. Am J Med Genet B Neuropsychiatr Genet. 2008;147B:1345–54. doi: 10.1002/ajmg.b.30867. [DOI] [PubMed] [Google Scholar]
- Lesch KP, Timmesfeld N, Renner TJ, Halperin R, Roser C, Nguyen TT, et al. Molecular genetics of adult ADHD: converging evidence from genome-wide association and extended pedigree linkage studies. J Neural Transm. 2008;115:1573–85. doi: 10.1007/s00702-008-0119-3. [DOI] [PubMed] [Google Scholar]
- Neale BM, Medland SE, Ripke S, Asherson P, Franke B, Lesch KP, et al. Metaanalysis of genome-wide association studies of attention-deficit/hyperactivity disorder. J Am Acad Child Adolesc Psychiatry. 2010;49:884–97. doi: 10.1016/j.jaac.2010.06.008. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Uhl GR, Drgonova J. Cell adhesion molecules: druggable targets for modulating the connectome and brain disorders? Neuropsychopharmacology. 2014;39 doi: 10.1038/npp.2013.240. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.