Skip to main content
NCBI home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2026 Feb 16.
Published in final edited form as: Neuroscience. 2025 Jan 3;567:150–162. doi: 10.1016/j.neuroscience.2024.12.037

Phasic Dopamine Release in Two Different Rat Models of Attention-Deficit/Hyperactivity Disorder: Spontaneously Hypertensive Rats (SHR) Versus Lphn3 Knockout Rats

Helen J K Sable 1, Nicholas B Paige 1, Patricia A Nalan 1, Rachel L Pace 1, Carina B Hicks 1, Samantha L Regan 2,3, Michael T Williams 2,3, Charles V Vorhees 2,3, Deranda B Lester 1
PMCID: PMC11789927  NIHMSID: NIHMS2047561  PMID: 39756609

Abstract

We examined DA activity in the medial prefrontal cortex (mPFC) and nucleus accumbens core (NAcc) in two Different Rat Models of Attention-Deficit/Hyperactivity Disorder: Spontaneously Hypertensive Rats (SHR) Versus Lphn3 Knockout Rats. We examined baseline stimulation-evoked phasic DA release, half-life, and DA autoreceptor (DAR) functioning in the mPFC and NAcc, as well as the response to nomifensine (10 mg/kg, IP), a DA transporter (DAT) blocker, on these measures in the NAcc. Both rat models were hypodopaminergic, with notable regional and mechanistic differences. The SHRs displayed decreased DA release in the NAcc compared to their control strain (i.e., WKY rats), with no differences in the mPFC, leading a much lower NAcc-to-PFC DA release ratio in SHRs compared to controls suggesting an imbalance in DA transmission between these regions. The Lphn3 KO rats were considered hypodopaminergic based on the reduced summed DA release in the mPFC and NAcc compared to WT controls, although differences were not observed when examining each site independently. Lphn3 KOs displayed increased DA half-life in the mPFC compared with Lphn3 WT rats, an indication of decreased DAT reuptake, with no differences in the NAcc. DAT blockade by nomifensine had a similar effect on DA release in the NAcc of SHRs and WKYs, but increased DA release in the NAcc of Lphn3 KOs to a greater extent than in WTs. These results suggest that the efficacy of pharmacotherapies used to treat externalizing disorders such as ADHD and/or SUD, likely differ between SHRs and Lphn3 KO rats.

Keywords: mesocorticolimbic, Dopamine, animal models, genetics, neurodevelopment, neurochemistry

Graphical Abstract

graphic file with name nihms-2047561-f0012.jpg

Introduction

A growing body of research has been aimed toward understanding the multifactorial association between catecholamine activity and externalizing disorders. Externalizing disorders (EDs) are characterized by disruptive behavior including impulsivity, poor-decision making, rule-breaking, hyperactivity, and inattention manifested outside the individual including oppositional defiant disorder (ODD), conduct disorder (CD), attention-deficit/hyperactivity disorder (ADHD), antisocial personality disorder (ASPD), and substance use disorder (SUD). ODD, CD, and ADHD typically present during childhood or early adolescence [7, 8], while ASPD and SUD usually manifest during late adolescence or young adulthood [9, 10]. Numerous studies indicate shared liability for EDs. For example, child/adolescent EDs are often comorbid [11] and highly predictive of ASPD and SUD later in life [12–14].

When examining extended pedigrees, different individuals within a single pedigree often exhibit various co-occurrences of EDs [11]. Likewise, twin and family studies have demonstrated that parent-child similarity of externalizing psychopathology is linked to a general liability for an ED, rather than a disorder-specific vulnerability [15, 16]. Additional research examining factors that contribute to this shared liability has determined it to be highly heritable and independent of shared environmental influence [15–18]. This is especially the case in late adolescence/young adulthood when externalizing liability is explained almost entirely by genetic influences [19, 20].

Data from a genome-wide, multigenerational sample identified linkage of ADHD as well as co-segregation of ADHD and other externalizing behaviors with markers on chromosome 4q13.2 [21–24]. Mapping of this region revealed variants in the latrophilin-3 gene [LPHN3 (ADGRL3); OMIM 616417] that predisposed individuals to ADHD [1, 2, 4], predicted ADHD severity and response to treatment [3–5], and predicted SUD in ADHD participants [6]. In SUD patients, LPHN3 was one of 86 “risk genes” identified [25]. The variants decrease expression or function of LPHN3 protein [26]. LPHN3 is an adhesion G protein-coupled receptor that is predominantly expressed in the brain and is essential for synapse formation [27].

Research in animal models has provided converging evidence that the Lphn3 gene plays a role in EDs. Lphn3 deletion in Drosophila induces hyperactivity [28], as does down-regulation of the ortholog lphn3.1 in zebrafish larvae [29]. Likewise, Lphn3−/− knockout (KO) mice have hyperactivity in the open field test [30, 31], increased premature responses (indicative of impulsivity) on a continuous performance test [30], increased reward motivation at high response ratios [32], and an enhanced acute locomotor response to a single injection of cocaine [31]. Similarly, Lphn3 KO rats are hyperactive, exhibit increased impulsivity [33], and show locomotor tolerance to a single injection of amphetamine [34] versus wildtype (Lphn3+/+; WT) controls. Impulsivity [35–37] and dysregulated motivation [38] are known risk factors for SUD.

Research showed that in vivo basal levels of dopamine (DA) were increased in the dorsal striatum of adolescent Lphn3 KO mice [31] while phasic DA release was increased along with a decrease in the duration and frequency of DA transients in ex vivo striatal slices taken from adult Lphn3 KO rats [39]. The DA transporter (DAT) is a likely target of Lphn3 gene expression changes as adult Lphn3 KO mice demonstrate overexpression of the gene Slc6a3 (DAT) in the dorsal striatum [32], and adult Lphn3 KO rats have increased DAT expression in the dorsal striatum [34]. This is significant as DAT expression is associated with ADHD, cocaine addiction, and alcoholism [see 40 for review] and DAT inhibitors are often used to treat ADHD [41]. Indeed, the ADHD medications methyphenidate and atomoxetine attenuate the hyperactivity observed in zebrafish larvae in which the lphn3.1 ortholog is down-regulated [29].

As seen above, most research examining the effects of alterations in Lphn3 expression on DA signaling were assessed in dorsal striatum. However, the externalizing behaviors associated with EDs are mediated, at least in part, by DA in the mesocorticolimbic pathway [42, 43]. Thus, the purpose of this study was to characterize mesocorticolimbic phasic DA release in the medial prefrontal cortex (mPFC) and nucleus accumbens core (NAcc) in Lphn3 KO and WT rats. We measured stimulation-evoked phasic DA release, half-life, and DA autoreceptor (DAR) functioning in the mPFC and NAcc, as well as the response to nomifensine (10 mg/kg, IP), a DAT blocker, on these measures in the NAcc using in vivo fixed potential amperometry. For comparison, we also collected these measures in Spontaneously Hypertensive Rats (SHR) as they have been robustly studied as an animal model of ADHD [44–48]. It was hypothesized that a) SHRs and Lphn3 KO rats would be hypodopaminergic in mPFC and NAcc relative to their respective controls, and that b) the DAT inhibitor nomifensine would increase evoked phasic DA release in the NAcc of SHRs and Lphn3 KO rats (relative to their respective controls) as well.

Method

Animals

All experiments were approved by the University of Memphis Institutional Animal Care and Use Committee (IACUC) and conducted in accordance with the National Institutes of Health Guidelines for the Care and Use of Laboratory Animals (NIH, 2015). This study was conducted in accordance with the ARRIVE (Animal Research: Reporting of In Vivo Experiments) guidelines. All necessary steps were taken to minimize animal suffering, and the study was designed to maximize the reliability and reproducibility of the findings.

Lphn3−/− KO rats were generated on a Sprague Dawley background (SD-IG, strain 001, Charles River, Charleston, NC) at the Cincinnati Children’s Transgenic Animal and Genome Editing Core by using CRISPR/Cas9 to delete exon3 (Regan et al., 2019). Only one rat per genotype per sex per litter was randomly selected with the use of a random numbers table and shipped to the University of Memphis when 30 ± 2 days old. This study included 20 Lphn3−/− knockout (KO; 11 males, 9 females) and 23 Lphn3+/+ wildtype (WT; 11 males, 12 females) rats. In addition, 22 Spontaneously Hypertensive Rats (SHRs; 11 males, 11 females) and 20 normotensive Wistar-Kyoto (WKY; 11 males, 9 females - SHR control strain) were purchased from Charles River (Kingston, NY) and shipped to University of Memphis at 45 ± 2 days old. Upon arrival at the University of Memphis Psychology vivarium, same-sex rats of the same strain or the same genotype were housed 2–3 per cage in standard plastic cages (45 cm x 24 cm x 30 cm) with corn cob bedding and ad libitum tap water in a room with a 12 h reverse light/dark cycle (lights off 0700 h) that was temperature- and humidity-controlled (temperature 23 ± 2 °C, humidity 50 ±10%). Rats remained on free feed (Teklad, 2018) until all rats in a shipment reached P60 after which they were put on a food restriction schedule to maintain 85–90% of their free-feeding weight because they first underwent a series of behavioral assessments [33, 49] prior to the collection of DA measurements which were collected when the rats were approximately five months old.

Surgery

All surgical procedures and amperometric recordings were made within a Faraday cage to increase the signal to noise ratio. Efforts were made to reduce the number of rats used and to minimize pain and discomfort. Rats were anesthetized with urethane (1.5 g/kg IP), assessed for pain response by foot and tail pinch, and mounted in a stereotaxic frame (David Kopf Instruments), ensuring a flat skull. Body temperature was maintained at 36 ± 0.5° C with a temperature-regulated heating pad (TC-1000, CWE). Three 1 mm diameter trephine holes were drilled in the skull for electrode placements. Stereotaxic coordinates are in mm from bregma, midline, and dura according to the rat atlas of Paxinos and Watson [50]. A concentric bipolar stimulating electrode (SNE-100, Microprobes) was inserted into the left medial forebrain bundle (MFB) (AP −4.2, ML +1.8, and DV −7.8), which includes dopaminergic axons from the ventral tegmental area to subcortical and cortical sites and has been previously used to elicit dopamine release by our lab and others [51–54]. A carbon fiber recording electrode (active recording surface of 500 μm length by 7 μm o.d.) was positioned in the left NAcc (AP −1.6, ML +1.5, and DV −7.4) or mPFC (AP −2.7, ML +0.8, DV −4.0). A stainless-steel auxiliary and Ag/AgCl reference electrode combination was placed on the surface of contralateral cortical tissue −2.0 mm from bregma. A fixed current of +0.8 V was applied with DA oxidation currents being continuously monitored (10 K samples/s) by an electrometer (ED401 e‐corder 401 and EA162 Picostat, eDAQ Inc.) filtered at 50 Hz. We and others have pharmacologically confirmed the evoked oxidation current in the mPFC and NAcc to be dependent upon DA efflux [51, 52, 55, 56].

Electrical Stimulation and Drug Administration

Following surgical setup, cathodal current pulses were delivered to the stimulating electrode via an optical isolator and programmable pulse generator (Iso-Flex/Master-8, AMPI). Stimulation parameters varied depending on the aspect of DA transmission being measured. Initially, 20 monophasic 0.5 ms duration pulses (800 μA) at 50 Hz were delivered every 30 s while the electrode depths were being adjusted to establish the optimal baseline response. These stimulation parameters were chosen to mimic phasic firing patterns of dopaminergic neurons in the VTA, as in our previous studies [51, 52]. Given our previous success recording stimulation-evoked DA in striatal regions [51, 52, 57, 58], an optimal response was first found in the NAcc to ensure proper placement of the stimulating electrode in the MFB. Recording electrodes were then moved to the mPFC, and stimulation parameters consisted of 50 monophasic 0.5 ms duration pulses (800 μA) at 50 Hz every 30 s for 10 min. From these mPFC recordings, we quantified DA release (the height of the evoked response) and the half-life of DA (a measurement of the time required for evoked DA to clear from the synapse). The DA half-life is defined as the time for 50% decrease from the maximum evoked increase to the prestimulus baseline level and is an indication of DAT functioning.

Following mPFC recordings, recording electrodes were moved back to the NAcc. DAR sensitivity was assessed using the same stimulation parameters as our previous studies [51, 55, 59]. A pair of test stimuli (T1 and T2, each 10 pulses at 50 Hz with 10 s between T1 and T2) was applied to the MFB every 30 s to evoke DA efflux. Six sets of prepulses (1, 5, 10, 20, 40, and 80; 0.5 ms pulse duration at 15 Hz) were delivered prior to T2 such that there was 0.3 s between the end of the prepulse train and initiation of T2. DAR mediated inhibition of evoked DA efflux is expressed in percent inhibition, i.e. the change in the amplitude of T2 with respect to T1 (T2/T1*100) for each set of prepulses. Thus, low-to-high DAR sensitivity is represented as a low-to-high percent inhibition of evoked DA efflux (i.e., high sensitivity resulted in a lower amplitude of T2 relative to T1). The DAR sensitivity test took approximately 20 min to complete.

Upon completion of the DAR sensitivity test, stimulation parameters were reset to 20 pulses at 50 Hz every 30 s. After a 10 min baseline recording of stimulation-evoked DA release and half-life, rats received an injection of nomifensine (20 mg/kg, i.p.). Electrical stimulations (20 pulses at 50 Hz every 30 sec) and amperometric recordings continued for 60 min following the nomifensine injection. Measurements of DA release and half-life were converted to percent change following nomifensine with pre-drug responses being 100%.

At the completion of each amperometric recording session, recording electrodes were removed, and a direct anodic current (400 μA for 10 s) was applied to the simulating electrode for placement confirmation. Recording electrodes were calibrated using an in vitro flow injection system and DA standards (0.2–1.2 μM) [60, 61], allowing measurements of DA oxidation current (μA) to be converted into DA concentration (μM).

Data Analysis

From mPFC and pre-nomifensine NAcc recordings, two-way between-subjects ANOVAs (SPSS, version 28.0) were used to determine the effect of sex and strain/genotype (SHR vs WKY and Lphn3−/− vs Lphn3+/+) on DA release and half-life. Likewise, two-way between-subjects ANOVAs were also used to determine the effect of sex and strain/genotype on the sum of mPFC and NAcc DA release and the ratio of baseline DA release in the NAcc to PFC. Baseline DA release from both brain regions was summed to assess overall mesocorticolimbic functioning, and differences in the ratio of release between the NAcc and PFC were examined as alterations in the function of these regions and the mPFC-NAc circuit have been associated with impaired reward initiation and processing, contributing to symptoms of impulsivity [62–64]. Three-way mixed ANOVAs were used to examine the effects of sex and strain/genotype (between-subjects factors) on DAR sensitivity across the pre-pulse conditions (within-subjects factor). Following nomifensine injection, two-way between-subjects ANOVAs were used to determine the effect of sex and strain/genotype on the percent change in DA release and half-life in the NAcc. Differences were assessed 20 min post injection, which has been shown to be the peak effect time of nomifensine [51, 52, 65].

Results

Successful placements and recordings for all dependent variables analyzed was not achieved for each and every rat. For those that were successful, the tips of the stimulating and recording electrodes were positioned within the anatomical boundaries of the mPFC, MFB, or NAcc (Figure 1). To improve readability, the final sample sizes included, as well as the statistical results, for each dependent variable are presented in Table 1.

Figure 1. Representative coronal sections of the rat brain (adapted from the atlas of Paxinos and Watson [48].

Figure 1.

Open in a new tab

For all rats in the study, gray shaded areas indicate the placements of recording electrodes in the medial prefrontal cortex (A), nucleus accumbens (B), and stimulating electrodes in the medial forebrain bundle (C). Numbers correspond to mm from bregma.

Table 1.

Analysis of Variance Results for Each Dependent Variable Analyzed

Lphn3−/− vs Lphn3+/+ SHR vs. WKY
mPFC DA Release KO: ♂n=8, ♀n=6; WT: ♂n=6, ♀n=9 SHR: ♂n=9, ♀n=7; WKY: ♂n=10, ♀n=11
Genotype/Strain F(1,25)=2.10, p=.160, ηp2=0.08 F(1,33)=0.27, p=.605, ηp2=0.01
Sex F(1,25)=8.41, p=.008, ηp2=0.25 F(1,33)=3.20, p=.083, ηp2=0.09
Sex x Genotype/Strain F(1,25)=0.40, p=.534, ηp2=0.02 F(1,33)=0.08, p=.777, ηp2<0.01
mPFC DA Half-life KO: ♂n=8, ♀n=6; WT: ♂n=6, ♀n=9 SHR: ♂n=9, ♀n=7; WKY: ♂n=10, ♀n=11
Genotype/Strain F(1,25)=4.35, p=.047, ηp2=0.15 F(1,33)=0.48, p=.494, ηp2=0.01
Sex F(1,25)=0.73, p=.401, ηp2=0.03 F(1,33)=0.04, p=.848, ηp2<.01
Sex x Genotype/Strain F(1,25)=0.90, p=.353, ηp2=0.04 F(1,33)=0.01, p=.922, ηp2<0.01
NAcc DA Release KO: ♂n=11, ♀n=9; WT: ♂n=11, ♀n=12 SHR: ♂n=11, ♀n=9; WKY: ♂n=11, ♀n=11
Genotype/Strain F(1,39)=3.40, p=.073, ηp2=0.08 F(1,38)=5.62, p=.023, ηp2=0.13
Sex F(1,39)=0.46, p=.502, ηp2=0.01 F(1,38)<0.01, p=.993, ηp2<0.01
Sex x Genotype/Strain F(1,39)=3.09, p=.087, ηp2=0.07 F(1,38)=0.27, p=.607, ηp2<0.01
NAcc DA Half-life KO: ♂n=11, ♀n=9; WT: ♂n=11, ♀n=12 SHR: ♂n=11, ♀n=9; WKY: ♂n=11, ♀n=11
Genotype/Strain F(1,39)=0.21, p=.650, ηp2<0.01 F(1,38)<0.01, p=.970, ηp2<.01
Sex F(1,39)=3.50, p=.069, ηp2=0.08 F(1,38)=0.02, p=.893, ηp2<0.01
Sex x Genotype/Strain F(1,39)=1.49, p=.229, ηp2=0.04 F(1,38)=0.55, p=.462, ηp2=0.01
Sum mPFC and NAcc DA Release KO: ♂n=8, ♀n=6; WT: ♂n=6, ♀n=9 SHR: ♂n=9, ♀n=7; WKY: ♂n=10, ♀n=11
Genotype/Strain F(1,25)=5.27, p=.030, ηp2=0.17 F(1,33)=3.40, p=.074, ηp2=0.09
Sex F(1,25)=0.97, p=.334, ηp2=0.04 F(1,33)=0.02, p=.896, ηp2<0.01
Sex x Genotype/Strain F(1,25)=3.11, p=.090, ηp2=0.11 F(1,33)=0.55, p=.463, ηp2=0.02
Ratio NAcc/mPFC DA Release KO: ♂n=8, ♀n=6; WT: ♂n=6, ♀n=9 SHR: ♂n=9, ♀n=7; WKY: ♂n=10, ♀n=11
Genotype/Strain F(1,25)=0.03, p=.866, ηp2<0.01 F(1,33)=4.25, p=.047, ηp2=.11
Sex F(1,25)=4.00, p=.057, ηp2=0.14 F(1,33)=1.06, p=.311, ηp2=0.03
Sex x Genotype/Strain F(1,25)=0.60, p=.446, ηp2=0.02 F(1,33)=1.02, p=.321, ηp2=0.03
NAcc DAR Sensitivity KO: ♂n=10, ♀n=9; WT: ♂n=11, ♀n=12 SHR: ♂n=11, ♀n=9; WKY: ♂n=11, ♀n=11
Genotype/Strain F(1,38)=2.74, p=.106, ηp2=0.07 F(1,38)=0.88, p=.355, ηp2=0.02
Sex F(1,38)=0.01, p=.929, ηp2<0.01 F(1,38)=1.38, p=.248, ηp2=0.04
Prepulses F(6, 228)=230.15, p<.001, ηp2=0.86 F(6, 228)=164.84, p<.001, ηp2=0.81
Sex x Genotype/Strain F(1,38)=2.76, p=.105, ηp2=0.07 F(1,38)=0.01, p=.910, ηp2<0.01
Sex x Prepulses F(6,228)=0.57, p=.751, ηp2=0.02 F(6,228)=0.76, p=.606, ηp2=0.02
Genotype/Strain x Prepulses F(6,228)=1.81, p=.098, ηp2=0.05 F(6,228)=0.57, p=.751, ηp2=0.02
Genotype/Strain x Sex x Prepulses F(6,228)=1.61, p=.144, ηp2=0.04 F(6,228)=0.26, p=.954, ηp2<0.01
% Change DA Release Post DAT Inhibition KO: ♂n=5, ♀n=5; WT: ♂n=5, ♀n=6 SHR: ♂n=10, ♀n=9; WKY: ♂n=11, ♀n=11
Genotype/Strain F(1,17)=10.84, p=.004, ηp2=0.39 F(1,37)=3.04, p=.090, ηp2=0.08
Sex F(1,17)=0.92, p=.352, ηp2=0.05 F(1,37)=0.11, p=.739, ηp2<0.01
Sex x Genotype/Strain F(1,17)=4.96, p=.040, ηp2=0.23 F(1,37)=1.91, p=.175, ηp2=0.05
% Change DA Half-Life Post DAT Inhibition KO: ♂n=5, ♀n=5; WT: ♂n=5, ♀n=6 ♂n=10, ♀n=9; WKY: ♂n=11, ♀n=11
Genotype/Strain F(1,17)=0.03, p=.875, ηp2<.01 F(1,37)=1.04, p=.314, ηp2=0.03
Sex F(1,17)=0.60, p=.450, ηp2=0.03 F(1,37)=3.50, p=.069, ηp2=0.09
Sex x Genotype/Strain F(1,17)=1.39, p=.255, ηp2=0.08 F(1,37)=0.32, p=.578, ηp2<0.01
Open in a new tab

Lphn3−/− vs Lphn3+/+ rats

PFC DA Release and Half-life.

Regarding baseline (pre-drug) stimulation-evoked DA release in the mPFC, a significant main effect of sex was observed, with males displaying greater DA release in the mPFC than females. There was no significant main effect of genotype or an interaction between sex and genotype on baseline mPFC DA release (Figure 2A and B). Regarding the baseline (pre-drug) half-life of DA in the mPFC, no main effect of sex was observed; however, there was a significant main effect of genotype, with Lphn3−/− rats displaying a longer DA half-life than Lphn3+/+ rats (Figure 2C). A longer half-life of DA indicates slower clearance and reduced DAT functioning [55, 66]. There was no significant interaction between sex and genotype on baseline half-life of DA in the mPFC.

Figure 2. Dopamine release in the mPFC of Lphn3−/− (KO) and Lphn3+/+ (WT) rats.

Figure 2.

Open in a new tab

Example responses from both genotypes are depicted (A), as well as means ± SEM for stimulation-evoked dopamine release (B) and the half-life of dopamine (C). Lphn3 KO rats did not differ from WTs in the magnitude of mPFC dopamine release, but Lphn3 KO rats displayed an increased half-life of dopamine in the mPFC compared with WTs, indicating slower clearance in Lphn3 KO rats.

NAcc DA Release and Half-life.

Regarding baseline (pre-drug) stimulation-evoked DA release in the NAcc, no significant main effect of sex or genotype (Figure 3A and B) was observed, and there was no significant interaction between sex and genotype. Regarding the baseline (pre-drug) half-life of DA in the NAcc, no main effects of sex or genotype were observed (Figure 3C), and there was no significant interaction between sex and genotype.

Figure 3. Baseline dopamine release in the NAcc of Lphn3−/− (KO) and Lphn3+/+ (WT) rats.

Figure 3.

Open in a new tab

Example baseline (pre-drug) responses are depicted (A), as well as means ± SEM for dopamine release (B) and the half-life of dopamine (C). Lphn3 KO rats did not differ from WTs in the magnitude of NAcc dopamine release or the half-life of dopamine in the NAcc.

Combined mPFC and NAcc DA Release.

Baseline DA release from both brain regions of Lphn3−/− and Lphn3+/+ rats were summed to assess overall mesocorticolimbic functioning. There was no main effect of sex; however, a significant main effect of genotype was observed, with Lphn3−/− rats displaying a reduced sum of DA release compared with Lphn3+/+ rats (Figure 4A). There was no significant interaction between sex and genotype on baseline DA release summed across both brain regions. The ratio of baseline DA release in the NAcc to mPFC was calculated to assess relative transmission between the two brain regions. There was no significant main effect of sex or genotype (Figure 4B) and no significant interaction between sex and genotype on the ratio of DA release in the NAcc to mPFC.

Figure 4. Combining dopamine release in the mPFC and NAcc of Lphn3−/− (KO) and Lphn3+/+ (WT) rats.

Figure 4.

Open in a new tab

Lphn3 KO rats displayed a reduced sum of mPFC and NAcc dopamine release compared with WTs (A); however, the ratio of NAcc dopamine release to mPFC dopamine release did not differ between Lphn3 KO and WT rats (B).

DAR sensitivity.

Autoreceptor-mediated inhibition of evoked DA release was expressed in terms of percent change of DA release between test stimulations (T2/T1 x 100) for each set of conditioning pre-pulses. A lower percentage indicates greater autoreceptor-mediated inhibition of DA release (Figure 5A). The main effect of genotype, the main effect of sex, and the sex x genotype interaction were all not significant. However, as expected, there was a significant main effect of the number of prepulses on autoreceptor-mediated DA release. Autoreceptor-mediated DA release decreased as the number of prepulses increased. As the number of prepulses increased, DAR functioning also increased, resulting in greater inhibition of DA release. Neither sex nor genotype altered the pattern of autoreceptor-mediated DA release across the conditioning prepulses as the prepulses x sex, prepulses x genotype (Figure 5B), and prepulse x sex x genotype interactions were all not significant.

Figure 5. Dopamine Autoreceptor Functioning in the NAcc of Lphn3−/− (KO) and Lphn3+/+ (WT) rats.

Figure 5.

Open in a new tab

Stimulation parameters were set to include two test stimulations (T1, T2) and a varying number of conditioning pre-pulses (pp). An example response is depicted (A). Greater decreases in dopamine release (% of T2/T1) indicates increased autoreceptor functioning. Lphn3 KO rats did not differ from WTs in NAc dopamine autoreceptor functioning (B).

Dopaminergic Response to DAT Inhibition.

The percent change in stimulation-evoked DA release and half-life in the NAcc were analyzed 20 min after an i.p. injection of the DAT inhibitor nomifensine in Lphn3−/− vs Lphn3+/+ rats, with the pre-drug (baseline) response representing 100%. Regarding the percent change in release following nomifensine, no main effect of sex was observed; however, there was a significant main effect of genotype, with Lphn3−/− rats displaying an increased percent change in DA release following nomifensine compared with Lphn3+/+ rats (Figure 6A and B). The sex x genotype interaction was also significant, indicating that DA release post nomifensine was altered by knocking out Lphn3 with greater effect in males than in females. Pairwise comparisons with Bonferroni corrections indicated a significant difference between male Lphn3−/− and Lphn3+/+ rats (p = .001) but not between female Lphn3−/− and Lphn3+/+ rats (p = .452) (Figure 6D). Regarding the percent change in the half-life of DA following nomifensine, no main effect of sex or genotype (Figure 6C) was observed, and there was no significant interaction between sex and genotype.

Figure 6. Dopamine release in the NAcc following nomifensine in Lphn3−/− (KO) and Lphn3+/+ (WT) rats.

Figure 6.

Open in a new tab

Example responses are depicted with the lighter profiles representing responses prior to administration of the dopamine transporter blocker nomifensine (A). Percent changes in release (B) and the half-life of dopamine (C) 20 min post nomifensine are presented as means ± SEM. Lphn3 KO rats displayed an increased percent change in dopamine release following nomifensine compared with WTs. The sex x genotype interaction was significant, and pairwise comparisons revealed a significant difference in release post-nomifensine between male Lphn3 KO and WT rats but not between female KO and WT rats (D).

SHR vs WKY rats

PFC DA Release and Half-life.

Regarding baseline (pre-drug) stimulation-evoked DA release in the mPFC of SHR and SHR control rats (WKY), no significant main effect of sex or strain (Figure 7A and B) was observed, and there was no significant interaction between sex and strain. Regarding the baseline (pre-drug) half-life of DA in the mPFC, no main effects of sex or strain (Figure 7C) was observed, and there was no significant interaction between sex and strain.

Figure 7. Dopamine release in the mPFC of SHR and control rats.

Figure 7.

Open in a new tab

Example responses from both strains are depicted (A), as well as means ± SEM for stimulation-evoked dopamine release (B) and the half-life of dopamine (C). SHR rats did not differ from controls (i.e., WYK rats) in the magnitude of mPFC dopamine release or the half-life of mPFC dopamine.

NAcc DA Release and Half-life.

Regarding baseline (pre-drug) stimulation-evoked DA release in the NAcc, no significant main effect of sex was observed; however, there was a significant main effect of strain, as SHR rats displayed reduced NAcc DA release compared with controls (Figure 8A and B). There was no significant interaction between sex and strain. Regarding the baseline (pre-drug) half-life of DA in the NAcc, no significant main effect of sex or strain (Figure 8C) was observed, and there was no significant interaction between sex and strain.

Figure 8. Baseline dopamine release in the NAcc of SHR and control rats.

Figure 8.

Open in a new tab

Example baseline (pre-drug) responses are depicted (A), as well as means ± SEM for stimulation-evoked dopamine release (B) and the half-life of dopamine (C). SHR rats displayed reduced NAcc dopamine release compared with control (i.e., WKY) rats, but SHR rats did not differ from controls in the half-life of dopamine in the NAc.

Combined mPFC and NAcc DA Release.

Baseline DA release from both brain regions of SHR and control rats were summed to assess overall mesocorticolimbic functioning. There was no significant main effect of sex or strain (Figure 9A). There was also no significant interaction between sex and strain. The ratio of baseline DA release in the NAcc to mPFC was calculated to assess relative transmission between the two brain regions in SHR and controls (i.e., WKY rats). There was no significant main effect of sex; however, a significant main effect of strain was observed, with the ratio of DA release in the NAcc to mPFC being less in SHR rats compared to WKY rats (Figure 9B). There was no significant interaction between sex and strain on the ratio of baseline DA release in the NAcc to mPFC.

Figure 9. Combining dopamine release in the mPFC and NAcc of SHR and control rats.

Figure 9.

Open in a new tab

The sums of mPFC and NAcc dopamine release did not differ between SHR and control rats (A); however, the ratio of NAcc to mPFC dopamine release was significantly lower in SHR rats compared with controls (B).

DAR sensitivity.

Autoreceptor-mediated inhibition of evoked DA release was expressed in terms of percent change of DA release between test stimulations (T2/T1 x 100) for each set of conditioning prepulses. A lower percentage indicates greater autoreceptor-mediated inhibition of DA release (Figure 10A). The main effect of strain, the main effect of sex, and the sex x strain interaction were all not significant. However, as expected, there was a significant main effect of the number of prepulses on autoreceptor-mediated DA release, with autoreceptor-mediated DA release decreasing as the number of prepulses increased. As the number of prepulses increased, DAR functioning also increased, resulting in greater inhibition of DA release. Neither sex nor strain altered this pattern of autoreceptor-mediated DA release across the conditioning prepulses as the prepulses x sex, prepulses x strain (Figure 10B), and prepulses x sex x strain interaction were all not significant.

Figure 10. Dopamine Autoreceptor Functioning in the NAcc of SHR and control rats.

Figure 10.

Open in a new tab

Stimulation parameters were set to include two test stimulations (T1, T2) and a varying number of conditioning pre-pulses (pp). An example response is depicted (A). Greater decreases in dopamine release (% of T2/T1) indicates increased autoreceptor functioning. SHR rats did not differ from controls (i.e., WYK rats) in NAcc dopamine autoreceptor functioning (B).

Dopaminergic Response to DAT Inhibition.

The percent changes in stimulation-evoked DA release and half-life in the NAcc were analyzed 20 min after an IP injection of the DAT inhibitor nomifensine in SHR and control rats, with the pre-drug (baseline) response representing 100%. Regarding the percent change in release following nomifensine, the significant main effect of sex and strain (Figure 11A and B), as well as the interaction between sex and strain were not significant. Regarding the percent change in the half-life of DA following nomifensine, no main effect of sex or strain (Figure 11C) was observed, and there was not a significant sex and strain interaction.

Figure 11. Dopamine release in the NAc following nomifensine in SHR and control rats.

Figure 11.

Open in a new tab

Example responses are depicted with the lighter profiles representing responses prior to administration of the dopamine transporter blocker nomifensine (A). Percent changes in release (B) and the half-life of dopamine (C) 20 min post nomifensine are presented as means ± SEM. SHR rats did not differ from controls in the percent change in dopamine release or half-life following nomifensine.

Discussion

The goal of this study was to characterize mesocorticolimbic phasic DA release in the mPFC and NAcc in two models of rats that exhibit ADHD-like phenotypes, SHR and Lphn3 KO rats, relative to their controls, WKY and Lphn3 WT rats, respectively. As previously mentioned, externalizing behaviors common ADHD and SUD are mediated by DA neurotransmission in the mesocorticolimbic pathway including the NAcc and mPFC [42, 43]. Overall, both Lphn3 KO and SHR rats displayed differences in mesocorticolimbic DA functioning compared with their controls, as both SHRs and Lphn3 KOs displayed a hypodopaminergic profile of mesocorticolimbic functioning, with notable regional and mechanistic differences between models. In the SHRs, differences were confined to the NAcc and not the PFC, while DA functioning differences were observed in both the mPFC and NAcc in Lphn3 KO rats. Compared with WT rats, Lphn3 KO rats had increased DA half-life in the mPFC and increased DA release in the NAcc following DAT inhibition with nomifensine, suggesting reduced DAT capacity in the KOs. These effects were absent in the SHRs. Instead, the differences between the SHRs and WKY rats were related to release mechanisms and only in the NAcc. There were also differences between the models when examining the sum of DA release in the NAcc and mPFC versus the ratio of NAcc to mPFC DA release. Lphn3 KO rats had a reduced sum of NAcc + mPFC DA release compared with WT rats, but the ratio of NAcc to mPFC DA release did not differ between Lphn3 KO and WT rats. The opposite was true when comparing the SHRs to the WKY rats, in that the sum of NAcc + mPFC DA release did not differ, but the ratio of NAcc to mPFC DA release was significantly lower in SHRs. There were no differences in autoreceptor functioning in either the SHRs or Lphn3 KO rats.

Relevance to Previous Behavioral Results

These results partially explain some of the behavioral differences that we have observed between the models on measures of impulsivity. We and others have used a delay discounting task to show that SHRs have an impairment in impulsive choice relative to WKY rats [49, 67, 68]. However, we found no difference between Lphn3 KO and WT rats on two different versions of a delay discounting task [49]. Inhibition of mPFC to NAcc projections increase impulsive choice in outbred rats that initially exhibited lower baseline impulsive choice [62]. Interestingly, Zhou et al. [63] found lower coherence in mPFC-NAc activity in SHRs versus Wistar rats when choosing the larger, delayed reward, providing evidence of a weaker mPFC-NAc functional connection in the former. We observed that the ratio of release in the NAcc to mPFC was lower in the SHRs than the WKY which also suggests an imbalance in coherence between the mesolimbic and mesocortical pathways. Overall, these results suggest that the lower ratio of phasic NAcc to mPFC DA release we observed in the SHRs may be contributing to their impaired impulsive choice behavior – a behavioral effect not observed in the Lphn3 KO rats arguably due to no observable difference in the NAcc:mPFC ratio compared with their WT counterparts.

Impulsivity is a multi-faceted construct and behavioral deficits on tasks of impulsive choice do not always coincide with deficits on tasks of impulsive action (or vice-versa) in rats or in humans [69–71]. We found exactly this, as both the Lphn3 KO and SHRs were impaired on a differential reinforcement of low rates (DRL) operant task, which is a task of impulsive action that requires withholding a response for a specified period of time to earn a reinforcer. Both the SHRs and Lphn3 KO rats had a lower ratio of reinforced to non-reinforced responses on a DRL 15 s task that occurred due to an increase in the proportion of responses with short, non-reinforced inter-response times (IRTs) along with a decrease in the proportion of responses with long, reinforceable IRTs [33]. The mechanism for the shared impulsive action deficit in the SHRs and Lphn3 KO rats in the context of the current study is unclear, given the discrepant findings between the models. We did not see significant differences in phasic DA release between the KO and WT rats in the mPFC or NAcc, although in the NAcc, there was a trend (p = .073) toward decreased phasic DA release in the KOs relative to the WT rats. Similarly, the SHRs had a significant decrease in phasic DA release in the NAcc, but not in the mPFC. There have been a number of studies examining the neural basis of DRL behavior, including studies examining the role of the mPFC and NAc in both establishing (i.e., acquisition) and maintaining DRL performance. Liao and Pattij [72] provide an excellent review of this literature. Based on a preponderance of the evidence using lesion and neurochemical approaches, they concluded that DA and serotonin in the ventral striatum (i.e., NAc) are involved in DRL acquisition and that the mPFC does not play a substantial role on the acquisition of this response. This suggests that the impaired DRL performance we observed in both the Lphn3 KO rats and SHRs [33] could be a function of decreased phasic DA release in the NAcc. Future research will be necessary to answer this question.

Implications for Development of ADHD Medications

The current results comparing DA functioning in the mPFC and NAcc of Lphn3 KO and SHRs also have implications related to medications development for the treatment of ADHD and perhaps even SUD. Methylphenidate (MPH) and dextroamphetamine (D-AMPH) are currently the most commonly prescribed psychostimulant medications for the treatment of ADHD [73–78]. MPH and D-AMPH both increase extracellular catecholamine concentrations by preventing the reuptake of DA and norepinephrine (NE) through modulation of their transporters (DAT and NET, respectively). However, unlike MPH, D-AMPH also produces reverse transport and inhibits catabolism of these neurotransmitters [75]. Thus, D-AMPH and MPH relieve an abnormal hypodopaminergic state in somewhat different ways that could be differentially beneficial based on the underlying mechanism. For example, given that Lphn3 KO rats had decreased DAT reuptake but there was not a significant difference in release, MPH would appear to be the more effective pharmacotherapy for the behavioral deficits observed in this ADHD model. To date, the ability of systemic MPH treatment to improve impulsive action deficits like the type we observed on DRL [33] has not been examined. Systemic MPH effectively attenuated hyperactivity in Drosophila in which Lphn3 has been knocked out [28] as well as in zebrafish in which the lphn3.1 orthologue has been knocked down [79]. On the other hand, MPH may not be the ideal option in SHRs, given that SHRs have decreased DA release. Rather, the reverse transport and limited catabolism facilitated by D-AMPH would arguably make it a better treatment alternative. However, impulsive action performance on a DRL task did not differ between SHRs and WKY rats following systemic MPH or D-AMPH administration [80], with one study demonstrating systemic MPH actually decreased performance in both strains [81]. Likewise, systemic MPH and D-AMPH were both ineffective at reducing impulsive choice in SHRs [82, 83].

Recall that we observed a decreased ratio of NAcc:mPFC phasic DA release in the SHRs relative to the WKY rats. This finding suggests that both the mechanism and regional specificity of a given pharmacotherapy must be considered in this model. To be the most effective at correcting this imbalance, a medication that selectively decreases DA and NE in mPFC or selectively increases DA and NE in the NAcc would be ideal. The NET-selective drug atomoxetine increases extracellular DA and NE in the PFC, but not in the NAc of rats [84]. In SHRs, atomoxetine and reboxetine (which are both selective NE reuptake inhibitors) increase the extracellular levels of NE and DA in the PFC as measured by microdialysis [85]. Given the selectivity of atomoxetine for the NET in PFC, this result would not be expected to correct the imbalance, and therefore do little to improve impulsivity in SHRs. Behavioral results bear this out, as systemic atomoxetine in SHRs did not reduce premature responding (i.e., a measure of impulsive action) on a five-choice serial reaction time task [86], and had no effect on a T-maze delay discounting procedure that measured impulsive choice [87].

Interestingly, impulsive choice measured on a delay discounting task was reduced in SHRs (but not in WKY rats) following systemic administration of fluphenazine, which is a nonselective DA receptor antagonist [83]. In vitro autoradiography has demonstrated up-regulation of both D1 and D2 receptors in the NAc but not the mPFC in adolescent (i.e., pre-hypertensive) SHRs compared with WKY rats [88]. Likewise, Vaughan et al. [89] found significantly higher levels of D2 receptor mRNA in the NAc of adolescent SHRs compared with age-matched WKY rats. Taken together, these results suggest that perhaps the effectiveness of fluphenazine in reducing impulsive choice in SHRs is because it is able to decrease DA neurotransmission in the NAc, thereby promoting a more balanced NAc to mPFC functional connection. Future research is also necessary to explore this possibility.

Lastly, it was previously reported that Lphn3 KO rats show increased DA transients in the dorsal striatum compared with WT littermates [90], suggesting increased DA signaling, whereas here we find evidence of DA hypofunction in NAcc and mPFC. These effects are in different brain regions involving two different streams. The DA hypofunction reported here is part of the NAcc-mPFC ventral stream implicated in motivation, whereas the previously reported increase in DA release by Regan et al. [87] was found in the dorsal striatum which is part of the dorsal stream involved in stimulus-response associations [91]. Differential changes in these pathways is possible, and therefore, only focusing on one portion of the striatum (ventral) is a limitation of the current study. Further experiments will be required to resolve this issue. Differences between the current findings and those of Regan et al. [87] may also be related to differences in the technique used. While Regan et al. measured endogenous transient responses with an average duration of 10 sec in brain slices, we measured stimulation-evoked phasic responses with an average duration of 3 sec in vivo. Differences observed in response frequencies would be negated by electrical stimulations. Thus, more research is needed to distinguish brain region and technique influences. It is also important to mention that our primary measure involved recording DA oxidation at the recording electrode placed in the mPFC or NAcc. While this was reflective of MFB-stimulated synaptic DA release, it also likely included oxidation of regional DA from sources other than direct stimulation of MFB DA axons. Future studies could use more targeted stimulation methods, such as optogenetics, to distinguish the influence of dopaminergic fiber activation from those of other neurotransmitter systems that also traverse the MFB. Such studies could compare the effects of dopaminergic drugs with non-dopaminergic drugs for ADHD treatment.

Summary

Mesocorticolimic DA dysfunction often accompanies externalizing disorders like ADHD and SUD. Both of the ADHD rat models examined here – the Lphn3 KO rat and the SHR – demonstrated DA hypofunctionality. The mechanism for this hypofunctionality differed, however, with Lphn3 KO rats exhibiting decreased DA transporter reuptake compared with WTs, while SHRs had decreased DA release compared with their WKY control stain. In addition, Lphn3 KO rats had an overall lower amount of phasic DA release across the NAcc and mPFC, but a ratio of NAcc to mPFC release that was similar to KO rats. The opposite was true in the SHRs, which had a lower NAcc to mPFC ratio than WKY rats, while the total amount measured in NAcc and mPFC did not differ. Future research is needed to both better understand how these differences contribute to the behavioral characteristics of ADHD (i.e., inattention, hyperactivity, and impulsivity), and to determine whether targeted selection of existing medications or development of new medications that work in a novel way are effective at alleviating these behavioral symptoms.

Highlights.

  • Mesocorticolimic dopamine (DA) dysfunction often accompanies externalizing disorders.

  • DA activity in Spontaneously Hypertensive Rats (SHR) and Lphn3−/− rats was examined.

  • SHRs and Lphn3−/− rats both displayed a hypodopaminergic mesocorticolimbic profile but with regional and mechanistic differences.

  • Lphn3−/− rats displayed differences related to DA transporter functioning while SHRs displayed differences related to DA release.

Acknowledgements:

Appreciation is extended to Donny Ray for assistance with lab animal care and Dr. Timothy Mandrell for his veterinary support.

Funding Sources:

This work was supported by bridge funding from The University of Memphis (HJKS) as well as a grant from The University of Memphis Faculty Research Grant Fund (HJKS & DBB), neither of which imply endorsement by the University of the research conclusions. This research was also supported by a Dissertation Completion Award from the Dean of the Graduate School (SLR) at the University of Cincinnati and NIH grant R01 ES032270 (CVV and MTW).

Footnotes

Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

Conflict of Interest Statement: All authors declare no conflict of interest.

References

  • 1.Acosta MT, et al. , Latent class subtyping of attention-deficit/hyperactivity disorder and comorbid conditions. J Am Acad Child Adolesc Psychiatry, 2008. 47(7): p. 797–807. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.Acosta MT, et al. , ADGRL3 (LPHN3) variants are associated with a refined phenotype of ADHD in the MTA study. Mol Genet Genomic Med, 2016. 4(5): p. 540–7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.Arcos-Burgos M, et al. , A common variant of the latrophilin 3 gene, LPHN3, confers susceptibility to ADHD and predicts effectiveness of stimulant medication. Mol Psychiatry, 2010. 15(11): p. 1053–66. doi: 10.1038/mp.2010.6. [DOI] [PubMed] [Google Scholar]
  • 4.Acosta MT, et al. , A two-locus genetic interaction between LPHN3 and 11q predicts ADHD severity and long-term outcome. Transl Psychiatry, 2011. 1: p. e17. 10.1038/tp.2011.14. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Bruxel EM, et al. , LPHN3 and attention-deficit/hyperactivity disorder: a susceptibility and pharmacogenetic study. Genes Brain Behav, 2015. 14(5): p. 419–27. [DOI] [PubMed] [Google Scholar]
  • 6.Arcos-Burgos M, et al. , ADGRL3 (LPHN3) variants predict substance use disorder. Transl Psychiatry, 2019. 9(1): p. 42. doi: 10.1038/s41398-019-0396-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Association, A.P., Disruptive, Impulse-Control, and Conduct Disorders, in Diagnostic and Statistical Manual of Mental Disorders, 5th Ed. 2013, American Psychiatric Association: Arlington, VA. doi: 10.1176/appi.books.9780890425596.dsm15. [DOI] [Google Scholar]
  • 8.Frick PJ and Nigg JT, Current issues in the diagnosis of attention deficit hyperactivity disorder, oppositional defiant disorder, and conduct disorder. Annu Rev Clin Psychol, 2012. 8: p. 77–107. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Association, A.P., Personality Disorders, in Diagnostic and Statistical Manual of Mental Disorders, 5th Ed. 2013, American Psychiatric Association: Arlington, VA. doi: 10.1176/appi.books.9780890425596.dsm18. [DOI] [Google Scholar]
  • 10.Association, A.P., Substance-Related and Addictive Disorders, in Diagnostic and Statistical Manual of Mental Disorders, 5th Ed. 2013, American Psychiatric Association: Arlington, VA. doi: 10.1176/appi.books.9780890425596.dsm16. [DOI] [Google Scholar]
  • 11.Palacio JD, et al. , Attention-deficit/hyperactivity disorder and comorbidities in 18 Paisa Colombian multigenerational families. J Am Acad Child Adolesc Psychiatry, 2004. 43(12): p. 1506–15. [DOI] [PubMed] [Google Scholar]
  • 12.Babinski LM, Hartsough CS, and Lambert NM, Childhood conduct problems, hyperactivity-impulsivity, and inattention as predictors of adult criminal activity. J Child Psychol Psychiatry, 1999. 40(3): p. 347–55. [PubMed] [Google Scholar]
  • 13.Elkins IJ, McGue M, and Iacono WG, Prospective effects of attention-deficit/hyperactivity disorder, conduct disorder, and sex on adolescent substance use and abuse. Arch Gen Psychiatry, 2007. 64(10): p. 1145–52. doi: 10.1001/archpsyc.64.10.1145. [DOI] [PubMed] [Google Scholar]
  • 14.Fergusson DM, Boden JM, and Horwood LJ, The developmental antecedents of illicit drug use: evidence from a 25-year longitudinal study. Drug Alcohol Depend, 2008. 96(1–2): p. 165–77. doi: 10.1016/j.drugalcdep.2008.03.003. [DOI] [PubMed] [Google Scholar]
  • 15.Bornovalova MA, et al. , Familial transmission and heritability of childhood disruptive disorders. Am J Psychiatry, 2010. 167(9): p. 1066–74. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Hicks BM, et al. , Family transmission and heritability of externalizing disorders: a twin-family study. Arch Gen Psychiatry, 2004. 61(9): p. 922–8. [DOI] [PubMed] [Google Scholar]
  • 17.Arcos-Burgos M, et al. , A common genetic network underlies substance use disorders and disruptive or externalizing disorders. Hum Genet, 2012. 131(6): p. 917–29. doi: 10.1007/s00439-012-1164-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Hicks BM, et al. , Genetic and environmental influences on the familial transmission of externalizing disorders in adoptive and twin offspring. JAMA Psychiatry, 2013. 70(10): p. 1076–83. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.Young SE, et al. , Genetic and environmental vulnerabilities underlying adolescent substance use and problem use: general or specific? Behav Genet, 2006. 36(4): p. 603–15. doi: 10.1007/s10519-006-9066-7. [DOI] [PubMed] [Google Scholar]
  • 20.Krueger RF, et al. , Etiologic connections among substance dependence, antisocial behavior and personality: Modeling the externalizing spectrum. Journal of Abnormal Psychology, 2002. 111(3): p. 411–24. doi: 10.1037/0021-843X.111.3.411. [DOI] [PubMed] [Google Scholar]
  • 21.Jain M, et al. , Attention-deficit/hyperactivity disorder and comorbid disruptive behavior disorders: evidence of pleiotropy and new susceptibility loci. Biol Psychiatry, 2007. 61(12): p. 1329–39. [DOI] [PubMed] [Google Scholar]
  • 22.Jain M, et al. , A cooperative interaction between LPHN3 and 11q doubles the risk for ADHD. Mol Psychiatry, 2012. 17(7): p. 741–7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Arcos-Burgos M, et al. , Attention-deficit/hyperactivity disorder in a population isolate: linkage to loci at 4q13.2, 5q33.3, 11q22, and 17p11. Am J Hum Genet, 2004. 75(6): p. 998–1014. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Arcos-Burgos M and Muenke M, Toward a better understanding of ADHD: LPHN3 gene variants and the susceptibility to develop ADHD. Atten Defic Hyperact Disord, 2010. 2(3): p. 139–47. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.Liu QR, et al. , Addiction molecular genetics: 639,401 SNP whole genome association identifies many "cell adhesion" genes. Am J Med Genet B Neuropsychiatr Genet, 2006. 141b(8): p. 918–25. doi: 10.1002/ajmg.b.30436. [DOI] [PubMed] [Google Scholar]
  • 26.Regan SL, et al. , A novel role for the ADHD risk gene latrophilin-3 in learning and memory in Lphn3 knockout rats. Neurobiol Dis, 2021. 158: p. 105456. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Sando R and Südhof TC, Latrophilin GPCR signaling mediates synapse formation. Elife, 2021. 10. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.van der Voet M, et al. , ADHD-associated dopamine transporter, latrophilin and neurofibromin share a dopamine-related locomotor signature in Drosophila. Mol Psychiatry, 2016. 21(4): p. 565–73. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29.Lange M, et al. , Pharmacological analysis of zebrafish lphn3.1 morphant larvae suggests that saturated dopaminergic signaling could underlie the ADHD-like locomotor hyperactivity. Prog Neuropsychopharmacol Biol Psychiatry, 2018. 84(Pt A): p. 181–189. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.Mortimer N, et al. , Dissociation of impulsivity and aggression in mice deficient for the ADHD risk gene Adgrl3: Evidence for dopamine transporter dysregulation. Neuropharmacology, 2019: p. doi: 10.1016/j.neuropharm.2019.02.039. [DOI] [PubMed] [Google Scholar]
  • 31.Wallis D, et al. , Initial characterization of mice null for Lphn3, a gene implicated in ADHD and addiction. Brain Res, 2012. 1463: p. 85–92. [DOI] [PubMed] [Google Scholar]
  • 32.Orsini CA, et al. , Behavioral and transcriptomic profiling of mice null for Lphn3, a gene implicated in ADHD and addiction. Mol Genet Genomic Med, 2016. 4(3): p. 322–43. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33.Sable HJK, et al. , An assessment of executive function in two different rat models of attention-deficit hyperactivity disorder: Spontaneously hypertensive versus Lphn3 knockout rats. Genes Brain Behav, 2021. 20(8): p. e12767. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 34.Regan SL, et al. , Knockout of latrophilin-3 in Sprague-Dawley rats causes hyperactivity, hyper-reactivity, under-response to amphetamine, and disrupted dopamine markers. Neurobiol Dis, 2019. 130: p. 104494. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35.Kozak K, et al. , The neurobiology of impulsivity and substance use disorders: implications for treatment. Ann N Y Acad Sci, 2018: p. doi: 10.1111/nyas.13977. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 36.Lee RSC, Hoppenbrouwers S, and Franken I, A Systematic Meta-Review of Impulsivity and Compulsivity in Addictive Behaviors. Neuropsychol Rev, 2019. 29(1): p. 14–26. doi: 10.1007/s11065-019-09402-x. [DOI] [PubMed] [Google Scholar]
  • 37.Vassileva J and Conrod PJ, Impulsivities and addictions: a multidimensional integrative framework informing assessment and interventions for substance use disorders. Philos Trans R Soc Lond B Biol Sci, 2019. 374(1766): p. 20180137. 10.1098/rstb.2018.0137. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38.Edwards S and Koob GF, Neurobiology of dysregulated motivational systems in drug addiction. Future Neurol, 2010. 5(3): p. 393–401. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 39.Regan SL, et al. , Knockout of latrophilin-3 in Sprague-Dawley rats causes hyperactivity, hyper-reactivity, under-response to amphetamine, and disrupted dopamine markers. Submitted. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 40.Pramod AB, et al. , SLC6 transporters: structure, function, regulation, disease association and therapeutics. Mol Aspects Med, 2013. 34(2–3): p. 197–219. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 41.Froehlich TE, McGough JJ, and Stein MA, Progress and promise of attention-deficit hyperactivity disorder pharmacogenetics. CNS Drugs, 2010. 24(2): p. 99–117. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 42.Beauchaine TP, Zisner AR, and Sauder CL, Trait Impulsivity and the Externalizing Spectrum. Annu Rev Clin Psychol, 2017. 13: p. 343–368. [DOI] [PubMed] [Google Scholar]
  • 43.Gatzke-Kopp LM, et al. , Neurological correlates of reward responding in adolescents with and without externalizing behavior disorders. J Abnorm Psychol, 2009. 118(1): p. 203–13. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 44.Kantak KM, et al. , Advancing the spontaneous hypertensive rat model of attention deficit/hyperactivity disorder. Behav Neurosci, 2008. 122(2): p. 340–57. [DOI] [PubMed] [Google Scholar]
  • 45.Meneses A, et al. , Spontaneously hypertensive rat (SHR) as an animal model for ADHD: a short overview. Rev Neurosci, 2011. 22(3): p. 365–71. [DOI] [PubMed] [Google Scholar]
  • 46.Sagvolden T and Johansen EB, Rat models of ADHD. Curr Top Behav Neurosci, 2012. 9: p. 301–15. [DOI] [PubMed] [Google Scholar]
  • 47.Sagvolden T, et al. , The spontaneously hypertensive rat model of ADHD--the importance of selecting the appropriate reference strain. Neuropharmacology, 2009. 57(7–8): p. 619–26. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 48.Sagvolden T, et al. , Rodent models of attention-deficit/hyperactivity disorder. Biol Psychiatry, 2005. 57(11): p. 1239–47. [DOI] [PubMed] [Google Scholar]
  • 49.Carbajal MS, et al. , Impulsive choice in two different rat models of ADHD-Spontaneously hypertensive and Lphn3 knockout rats. Front Neurosci, 2023. 17: p. 1094218. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 50.Paxinos G and Watson C, The Rat Brain in Stereotaxic Coordinates. 4th ed. ed. 1998, San Diego, CA: Academic Press. [Google Scholar]
  • 51.Holloway ZR, et al. , Comparing phasic dopamine dynamics in the striatum, nucleus accumbens, amygdala, and medial prefrontal cortex. Synapse, 2018: p. e22074. [DOI] [PubMed] [Google Scholar]
  • 52.Freels TG, et al. , Risky decision-making predicts dopamine release dynamics in nucleus accumbens shell. Neuropsychopharmacology, 2020. 45(2): p. 266–275. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 53.Ikemoto S and Panksepp J, The role of nucleus accumbens dopamine in motivated behavior: a unifying interpretation with special reference to reward-seeking. Brain Res Brain Res Rev, 1999. 31(1): p. 6–41. [DOI] [PubMed] [Google Scholar]
  • 54.Saddoris MP, et al. , Mesolimbic dopamine dynamically tracks, and is causally linked to, discrete aspects of value-based decision making. Biol Psychiatry, 2015. 77(10): p. 903–911. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 55.Mittleman G, et al. , Dopamine dynamics associated with, and resulting from, schedule-induced alcohol self-administration: analyses in dopamine transporter knockout mice. Alcohol, 2011. 45(4): p. 325–39. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 56.Tye SJ, Miller AD, and Blaha CD, Ventral tegmental ionotropic glutamate receptor stimulation of nucleus accumbens tonic dopamine efflux blunts hindbrain-evoked phasic neurotransmission: implications for dopamine dysregulation disorders. Neuroscience, 2013. 252: p. 337–45. [DOI] [PubMed] [Google Scholar]
  • 57.Forster GL and Blaha CD, Laterodorsal tegmental stimulation elicits dopamine efflux in the rat nucleus accumbens by activation of acetylcholine and glutamate receptors in the ventral tegmental area. Eur J Neurosci, 2000. 12(10): p. 3596–604. [DOI] [PubMed] [Google Scholar]
  • 58.Lester DB, Miller AD, and Blaha CD, Muscarinic receptor blockade in the ventral tegmental area attenuates cocaine enhancement of laterodorsal tegmentum stimulation-evoked accumbens dopamine efflux in the mouse. Synapse, 2010. 64(3): p. 216–23. [DOI] [PubMed] [Google Scholar]
  • 59.Fielding JR, et al. , Stimulation-evoked dopamine release in the nucleus accumbens following cocaine administration in rats perinatally exposed to polychlorinated biphenyls. Toxicol Sci, 2013. 136(1): p. 144–53. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 60.Michael DJ and Wightman RM, Electrochemical monitoring of biogenic amine neurotransmission in real time. J Pharm Biomed Anal, 1999. 19(1–2): p. 33–46. [DOI] [PubMed] [Google Scholar]
  • 61.Prater W, et al. , Examining the Effects of Common Laboratory Methods on the Sensitivity of Carbon Fiber Electrodes in Amperometric Recordings of Dopamine. Journal of Behavioral and Brain Science, 2018. 08: p. 117–125. [Google Scholar]
  • 62.Wenzel JM, et al. , Selective chemogenetic inactivation of corticoaccumbal projections disrupts trait choice impulsivity. Neuropsychopharmacology, 2023. 48(12): p. 1821–1831. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 63.Zhuo L, et al. , The function of mPFC-NAc circuit in decision impulsivity: A study based on an animal model. Acta Psychologica Sinica, 2023. 55(4): p. 556–571. [Google Scholar]
  • 64.Gill TM, Castaneda PJ, and Janak PH, Dissociable roles of the medial prefrontal cortex and nucleus accumbens core in goal-directed actions for differential reward magnitude. Cereb Cortex, 2010. 20(12): p. 2884–99. [DOI] [PubMed] [Google Scholar]
  • 65.Estes MK, et al. , Chronic oxytocin administration alters mesolimbic dopamine release in mice. Neuroscience, 2019. 408: p. 226–238. [DOI] [PubMed] [Google Scholar]
  • 66.Gonon F, et al. , Geometry and kinetics of dopaminergic transmission in the rat striatum and in mice lacking the dopamine transporter. Prog Brain Res, 2000. 125: p. 291–302. [DOI] [PubMed] [Google Scholar]
  • 67.Fox AT, Hand DJ, and Reilly MP, Impulsive choice in a rodent model of attention-deficit/hyperactivity disorder. Behav Brain Res, 2008. 187(1): p. 146–52. [DOI] [PubMed] [Google Scholar]
  • 68.Sjoberg EA, et al. , The irrelevancy of the inter-trial interval in delay-discounting experiments on an animal model of ADHD. Behav Brain Res, 2021. 408: p. 113236. [DOI] [PubMed] [Google Scholar]
  • 69.Solanto MV, et al. , The ecological validity of delay aversion and response inhibition as measures of impulsivity in AD/HD: a supplement to the NIMH multimodal treatment study of AD/HD. J Abnorm Child Psychol, 2001. 29(3): p. 215–28. [DOI] [PubMed] [Google Scholar]
  • 70.Broos N, et al. , The relationship between impulsive choice and impulsive action: a cross-species translational study. PLoS One, 2012. 7(5): p. e36781. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 71.van den Bos W, et al. , Connectivity strength of dissociable striatal tracts predict individual differences in temporal discounting. J Neurosci, 2014. 34(31): p. 10298–310. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 72.Liao RM and Pattij T, Neural basis of operant behaviors maintained on the differential-reinforcement-of-low-rate (DRL) schedule in rodents. Brain Res Bull, 2022. 185: p. 1–17. [DOI] [PubMed] [Google Scholar]
  • 73.Bowton E, et al. , Dysregulation of dopamine transporters via dopamine D2 autoreceptors triggers anomalous dopamine efflux associated with attention-deficit hyperactivity disorder. J Neurosci, 2010. 30: p. 6048–57. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 74.Del Campo N, et al. , The roles of dopamine and noradrenaline in the pathophysiology and treatment of attention-deficit/hyperactivity disorder. Biol Psychiatry, 2011. 69: p. e145–57. [DOI] [PubMed] [Google Scholar]
  • 75.Madras BK, Miller GM, and Fischman AJ, The dopamine transporter and attention-deficit/hyperactivity disorder. Biol Psychiatry, 2005. 57: p. 1397–409. [DOI] [PubMed] [Google Scholar]
  • 76.Russell VA, Dopamine hypofunction possibly results from a defect in glutamate-stimulated release of dopamine in the nucleus accumbens shell of a rat model for attention deficit hyperactivity disorder--the spontaneously hypertensive rat. Neurosci Biobehav Rev, 2003. 27: p. 671–82. [DOI] [PubMed] [Google Scholar]
  • 77.Russell VA, Overview of animal models of attention deficit hyperactivity disorder (ADHD). Curr Protoc Neurosci, 2011. Chapter 9: p. Unit9.35. [DOI] [PubMed] [Google Scholar]
  • 78.Sagvolden T, Behavioral validation of the spontaneously hypertensive rat (SHR) as an animal model of attention-deficit/hyperactivity disorder (AD/HD). Neurosci Biobehav Rev, 2000. 24: p. 31–9. [DOI] [PubMed] [Google Scholar]
  • 79.Lange M, et al. , The ADHD-susceptibility gene lphn3.1 modulates dopaminergic neuron formation and locomotor activity during zebrafish development. Mol Psychiatry, 2012. 17(9): p. 946–54. [DOI] [PubMed] [Google Scholar]
  • 80.Ferguson SA, et al. , Baseline behavior, but not sensitivity to stimulant drugs, differs among spontaneously hypertensive, Wistar-Kyoto, and Sprague-Dawley rat strains. Neurotoxicol Teratol, 2007. 29(5): p. 547–61. [DOI] [PubMed] [Google Scholar]
  • 81.Orduna V, Valencia-Torres L, and Bouzas A, DRL performance of spontaneously hypertensive rats: dissociation of timing and inhibition of responses. Behav Brain Res, 2009. 201(1): p. 158–65. [DOI] [PubMed] [Google Scholar]
  • 82.Hand DJ, Fox AT, and Reilly MP, Differential effects of d-amphetamine on impulsive choice in spontaneously hypertensive and Wistar-Kyoto rats. Behav Pharmacol, 2009. 20(5–6): p. 549–53. [DOI] [PubMed] [Google Scholar]
  • 83.Wooters TE and Bardo MT, Methylphenidate and fluphenazine, but not amphetamine, differentially affect impulsive choice in spontaneously hypertensive, Wistar-Kyoto and Sprague-Dawley rats. Brain Res, 2011. 1396: p. 45–53. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 84.Bymaster FP, et al. , Atomoxetine increases extracellular levels of norepinephrine and dopamine in prefrontal cortex of rat: a potential mechanism for efficacy in attention deficit/hyperactivity disorder. Neuropsychopharmacology, 2002. 27(5): p. 699–711. [DOI] [PubMed] [Google Scholar]
  • 85.Umehara M, et al. , Effects of serotonin-norepinephrine reuptake inhibitors on locomotion and prefrontal monoamine release in spontaneously hypertensive rats. Eur J Pharmacol, 2013. 702(1–3): p. 250–7. [DOI] [PubMed] [Google Scholar]
  • 86.Dommett EJ, Using the five-choice serial reaction time task to examine the effects of atomoxetine and methylphenidate in the male spontaneously hypertensive rat. Pharmacol Biochem Behav, 2014. 124: p. 196–203. [DOI] [PubMed] [Google Scholar]
  • 87.Turner M, et al. , Effects of atomoxetine on locomotor activity and impulsivity in the spontaneously hypertensive rat. Behav Brain Res, 2013. 243: p. 28–37. [DOI] [PubMed] [Google Scholar]
  • 88.Kirouac GJ and Ganguly PK, Up-regulation of dopamine receptors in the brain of the spontaneously hypertensive rat: an autoradiographic analysis. Neuroscience, 1993. 52(1): p. 135–41. [DOI] [PubMed] [Google Scholar]
  • 89.Vaughan CE, van den Buuse M, and Roland BL, Brain dopamine D2 receptor mRNA levels are elevated in young spontaneously hypertensive rats. Neurosci Res, 1999. 34(4): p. 199–205. [DOI] [PubMed] [Google Scholar]
  • 90.Regan SL, et al. , Enhanced Transient Striatal Dopamine Release and Reuptake in Lphn3 Knockout Rats. ACS Chem Neurosci, 2020. 11(8): p. 1171–1177. [DOI] [PubMed] [Google Scholar]
  • 91.Hart G, Leung BK, and Balleine BW, Dorsal and ventral streams: the distinct role of striatal subregions in the acquisition and performance of goal-directed actions. Neurobiol Learn Mem, 2014. 108: p. 104–18. [DOI] [PMC free article] [PubMed] [Google Scholar]

RESOURCES