Clinical trial NCT03334721
Conditions: Bipolar I Disorder Bipolar II Disorder Cannabis Use Disorder Substance Use Disorders
Sponsor: Medical University of South Carolina
Start date: 2017-10-01; Completion date: 2019-07-01
Enrollment: 23 participants; Allocation: RANDOMIZED; Intervention model: CROSSOVER

Brief summary:
The proposed 2-week, double-blind, crossover, proof of concept study aims to measure and manipulate core neurochemical (i.e., dysregulated brain GABA/glutamate homeostasis) and neurobehavioral (i.e., elevated impulsivity) dysfunctions characteristic of individuals with cannabis use disorder (CUD) and Bipolar Disorder (BD), using a medication that has been shown to increase cortical GABA (i.e., gabapentin) levels in past research, and to evaluate medication-related changes in response inhibition (go no-go) and cannabis cue reactivity functional Magnetic Resonance Imaging tasks, as well as cannabis use, mood symptoms (including anxiety and sleep), and impulsivity in individuals with CUD+BD.

Detailed description:
Bipolar disorder (BD) is the Axis I condition most strongly associated with cannabis use disorder (CUD); there is a six-fold increase in the prevalence of CUD in individuals with BD relative to the general population. Individuals with co-occurring CUD and BD (CUD+BD) have substantially worse clinical outcomes than those with either BD or CUD alone. Response to mood stabilizing medications appears to be poor, yet little is known about optimal treatment for CUD+BD, as there have been no randomized medication trials for CUD+BD to date. Convergent evidence supports dysregulated brain γ-Aminobutyric acid (GABA)/glutamate homeostasis as a candidate target for pharmacological intervention in CUD+BD. Preclinical and clinical studies have demonstrated that CUD and BD are each associated with prefrontal GABA and glutamate disturbances and that impulsivity, a core neurobehavioral feature of both CUD and BD and a key Research Domain Criteria (RDoC) construct, is causally related to GABAergic/glutamatergic functioning. Gabapentin has been consistently shown in preclinical research to modulate GABA and glutamate transmission. In human Proton Magnetic Resonance Spectroscopy (1H-MRS) studies, both acute and chronic gabapentin dosing have been shown to increase brain GABA levels, however, few studies have investigated gabapentin effects on glutamate levels. Researchers propose that gabapentin may impact clinical outcomes in CUD+BD individuals both directly and indirectly through their impact on impulsivity.

Arms: arm 1: Week 1: 1-week condition will consist of an in-person study visit for assessment and dispensing of medication (Day 1), titration to maximum dose (i.e., 1,200mg gabapentin) (Days 1-5), MRI (Day 5), and medication washout (Days 5-7).

Week 2: 1-week condition will consist of an in-person study visit for assessment and dispensing of medication (Day 1), titration to maximum dose (Days 1-5), MRI (Day 5), and medication washout (Days 5-7). arm 2: Week 1: 1-week condition will consist of an in-person study visit for assessment and dispensing of medication (Day 1), titration to maximum dose (Days 1-5), MRI (Day 5), and medication washout (Days 5-7).

Week 2: 1-week condition will consist of an in-person study visit for assessment and dispensing of Gabapentin medication (Day 1), titration to maximum dose (i.e., 1,200mg gabapentin) (days 1-5), MRI (Day 5), and medication washout (Days 5-7).
Interventions: intervention 1: Gabapentin intervention 2: Placebo Oral Capsule
Intervention descriptions: intervention 1: 5 day trial of gabapentin with titration to 1,200mg intervention 2: 5 day trial of matched placebo

Protocol documents:
Prot_SAP_000.pdf: 
 
 
 
 
 
 
 
 
Gabapentin for Bipolar & Cannabis Use Disorders: Relation to Brain GABA/Glutamate 
NCT03334721 
10/25/2017 
 
 


 
 
 
 
 
 
 
Gabapentin for Bipolar & Cannabis Use Disorders: Relation to Brain GABA/Glutamate 
PI: James J. Prisciandaro, PhD 
Protocol 
10/16/17 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 


Specific Aims 
Bipolar disorder (BD) is the Axis I condition most strongly associated with cannabis use disorder (CUD); there is 
a six-fold increase in the prevalence of CUD in individuals with BD relative to the general population. Individuals 
with co-occurring CUD and BD (CUD+BD) have substantially worse clinical outcomes than those with either BD 
or CUD alone. Response to mood stabilizing medications appears to be poor, yet little is known about optimal 
treatment for CUD+BD, as there have been no randomized medication trials for CUD+BD to date. Convergent 
evidence supports dysregulated brain γ-Aminobutyric acid (GABA)/glutamate homeostasis as a candidate target 
for pharmacological intervention in CUD+BD. Preclinical and clinical studies have demonstrated that CUD and 
BD are each associated with prefrontal GABA and glutamate disturbances and that impulsivity, a core 
neurobehavioral feature of both CUD and BD and a key Research Domain Criteria (RDoC) construct, is causally 
related to GABAergic/glutamatergic functioning. Gabapentin has been consistently shown in preclinical research 
to modulate GABA and glutamate transmission. In human Proton Magnetic Resonance Spectroscopy (1H-MRS) 
studies, both acute and chronic gabapentin dosing have been shown to increase brain GABA levels, however, 
few studies have investigated gabapentin effects on glutamate levels. We propose that gabapentin may impact 
clinical outcomes in CUD+BD individuals both directly and indirectly through their impact on impulsivity. 
The proposed 2-week, double-blind, crossover, proof of concept study will focus on GABA, while exploring 
glutamate, disturbances in CUD+BD and will evaluate: a) whether gabapentin, a medication that has been 
demonstrated to increase cortical GABA concentrations in healthy controls and individuals with epilepsy, may 
similarly act to increase dorsal anterior cingulate and basal ganglia GABA levels in individuals with CUD+BD, 
and b) whether increased dorsal anterior cingulate and basal ganglia GABA levels will be associated with 
increased functional brain activity to response inhibition (“go no-go”) cues (a well-studied neurobehavioral probe 
of impulsivity) as well as decreased functional brain activity to cannabis cues. Effects of gabapentin on cannabis 
use, mood symptoms (including anxiety and sleep), and impulsivity will be explored.  
Hypothesis 1:  Gabapentin will increase dorsal anterior cingulate and basal ganglia GABA concentrations, 
relative to placebo, in individuals with CUD+BD.  
Hypothesis 2:  Gabapentin-related increases in dorsal anterior cingulate and basal ganglia GABA 
concentrations will be associated with, a) increased brain activity to response inhibition (“no-go”) cues relative to 
response activation (“go”) cues and b) decreased functional brain activity to visual cannabis cues relative to 
neutral cues. 
Exploratory Hypotheses: 1) Given the lack of data on gabapentin and glutamate, associations between 
gabapentin and dorsal anterior cingulate/basal ganglia glutamate concentrations, and between gabapentin-
related changes in glutamate concentrations and functional brain activity to response inhibition and cannabis 
cues, will be explored. 2) Associations between gabapentin-related changes in dorsal anterior cingulate/basal 
ganglia GABA and glutamate concentrations and cannabis use, mood symptoms (including anxiety and sleep), 
and impulsivity over the course of the study will be explored.  
In summary, the proposed 2-week, double-blind, crossover, proof of concept study aims to measure and 
manipulate core neurochemical (i.e., dysregulated brain GABA/glutamate homeostasis) and neurobehavioral 
(i.e., elevated impulsivity) dysfunctions characteristic of individuals with CUD and BD, using a medication that 
has been shown to increase cortical GABA (i.e., gabapentin) levels in past research, and to evaluate medication-
related changes in response inhibition (go no-go) and cannabis cue reactivity functional Magnetic Resonance 
Imaging tasks, as well as cannabis use, mood symptoms (including anxiety and sleep), and impulsivity in 
individuals with CUD+BD. Positive results may support investigation of gabapentin for the treatment of CUD+BD 
in large-scale, randomized clinical trials. The proposed study may also provide successful demonstration of a 
neurobehavioral, multimodal neuroimaging platform for evaluating the potential promise of other GABAergic 
drugs for CUD and/or BD, as well as other conditions marked by GABA/glutamate dysfunction. 
 
 
 
 
 
 
 
 


A. SIGNIFICANCE 
A.1. Overview. There is a six-fold increase in the prevalence of cannabis use disorder (CUD) in individuals with 
bipolar disorder (BD) relative to the general population1. Co-occurring CUD and BD (CUD+BD) is associated 
with more frequent mood cycling1, poorer quality of life1, disability2 and psychosis3 relative to BD alone, even in 
individuals receiving state-of-the-art pharmacotherapy for BD4. Response to mood stabilizing medications is 
poor5, 6, yet little is known about optimal treatment as there have been no controlled trials (RCTs) for CUD+BD. 
Evidence supports disrupted brain γ-Aminobutyric acid (GABA)/glutamate (GLU) homeostasis as a target for 
pharmacological intervention in CUD+BD. Gabapentin may work through this mechanism to treat CUD+BD. 
A.2. GABA and GLU Dysregulation in CUD and BD. GABA and GLU, the main inhibitory and excitatory 
neurotransmitters (NTs) in mammals, respectively, are principally involved in the coordination of cortical activity, 
synaptic plasticity and modulation of other NT systems7, 8. The extant literature supports a role for dysregulated 
GABA and GLU transmission in CUD and BD. Preclinical research suggests that the reorganization of reward 
circuitry in substance use disorders (SUD) to preferentially respond to drug cues, manifesting clinically as drug 
craving and seeking, may be due to substance-induced neuroplasticity mediated by GLU and GABA9, 10. 
Cannabinoids have been shown to decrease GABAA-mediated inhibitory, and NMDA/AMPA-mediated excitatory, 
transmission11 via activation of cannabinoid type-1 (CB1) receptors located on presynaptic GABA/GLU neurons12 
that are particularly abundant in cortex and basal ganglia (BG)13. BD studies have demonstrated links between 
genes responsible for coding ionotropic GLU receptor subunits, BD14, and lithium response15, as well as reduced 
levels of cerebrospinal fluid (CSF) and plasma GABA16, 17 and differences in GABA receptor genes18-20. Proton 
Magnetic Resonance Spectroscopy (1H-MRS) studies provide the opportunity to better understand these issues 
in humans. 1H-MRS studies in CUD individuals have demonstrated decreased GLU and GABA levels in anterior 
cingulate cortex (ACC)21, 22 as well as decreased GLU in right BG (rBG)23, 24. 1H-MRS studies of BD have 
demonstrated elevated prefrontal GLU across mood states25-31, and state-of-the-art (MEGA-PRESS) GABA 
studies have found abnormal ACC and occipital cortex GABA levels as well32-34. Impulsivity, the tendency to 
respond without forethought, has been hypothesized as a “critical link” between SUD and BD35; it is a core 
neurobehavioral feature of both CUD36 and BD37 and is causally related to GABA/GLU function38, 39. Preclinical 
studies have shown that injections of NMDA receptor antagonists39, as well as the GABAA receptor agonist 
muscimol38, are associated with impulsive behavior. 1H-MRS studies have demonstrated a positive association 
between anterior cingulate cortex (ACC) glutamate and impulsivity40 and a negative association between 
dorsolateral PFC41 and ACC40 GABA and impulsivity across clinical populations. Finally, fMRI investigations, 
which have primarily focused on the response inhibition facet of impulsivity, have consistently demonstrated 
differences in prefrontal activation to inhibition cues in both BD42 and CUD43 individuals relative to controls. In 
sum, studies have found that CUD and BD are each associated with prefrontal GABA/GLU disturbances and 
that impulsivity, a core neurobehavioral feature of both CUD and BD, is causally related to GABA/GLU function. 
Medications that normalize brain GABA/GLU may, therefore, impact clinical outcomes in CUD and BD both 
directly and indirectly through their impact on impulsivity (a key Research Domain Criteria [RDoC] construct). 
A.3. Gabapentin for Restoring GABA/GLU Homeostasis. 1H-MRS studies have consistently demonstrated 
that three GABAergic medications increase brain GABA levels: gabapentin, topiramate, and vigabatrin44. 
Gabapentin has been shown to significantly raise occipital GABA levels 1-6 hours following a single dose (900-
1200mg) in healthy controls45, 46 and epileptics47. Long-term gabapentin dosing has also been shown to 
significantly increase occipital GABA in controls (2400mg/day)46 and epileptics (1200-3600mg/day)47, 48. Most 
studies reported average increases of 25-50%, with individuals with lower baseline levels showing the largest 
increases in GABA with gabapentin45, 47. Whereas topiramate and vigabatrin are associated with significant side 
effects including cognitive dysfunction49, particularly during rapid dose-titration, gabapentin is well-tolerated and 
safe. Although preclinical studies have consistently found decreased GLU release with gabapentin 
administration, the only 1H-MRS gabapentin study in humans to measure GLU found that acute gabapentin 
(900mg) did not change GLU levels45; multiple doses may be necessary to elicit a GLU response. Preclinical 
studies have also demonstrated that pregabalin, a GABA-analogue with high structural similarity to gabapentin, 
blocks motor signs and anxiety behaviors associated with cannabis withdrawal50. Basic human studies have 
found that both gabapentin and the GABAB-selective agonist, baclofen, shift the discriminative-stimulus effects 
of Δ9-THC leftward/upward, suggesting that these agents may improve CUD outcomes by producing cannabis-
like interoceptive effects51, 52. Preclinical studies of gabapentin that have focused on other substances of abuse 
(e.g., ethanol, cocaine) have demonstrated decreased, a) self-administration53, 54, b) stressor/cue-induced 
reinstatement53, c) expression/development of stimulant sensitization55, 56, d) drug-induced place preference56, 
and e) anxiogenic effects of withdrawal54. Effects of gabapentin in these studies appear to be mediated, in part, 
by normalization of GABAergic transmission in central amygdala54 and elevation of α2/δ-1 subunit of voltage-


gated calcium channels56. Research has also demonstrated that the efficacy of gabapentin may be moderated 
by variation in GABAA receptor subunits α 1 and 3; as such, genetic investigation for the present study will focus 
on associated single nucleotide polymorphisms (e.g., rs10068980, rs1112122, rs1157122, rs4828696, 
rs511310, 
rs6883877, 
rs6892782, 
aggregated 
in 
https://www.pharmgkb.org/chemical/PA449720 
#tabview=tab1&subtab=31) along with variation in genes that code for NMDA and AMPA receptors, as these 
receptors appear to be impacted by gabapentin treatment (Rose and Kam, 2002); interestingly, many of these 
same SNPs have been shown to differentiate individuals with and without mood disorders (Brambilla et al., 
2003). A recent RCT demonstrated reduced cannabis use and withdrawal in adults with CUD who were treated 
with gabapentin (1200mg/day)57; no other medications have demonstrated efficacy for reducing cannabis use in 
adults with CUD58. Despite a long history of positive reports from open-label studies in BD59, two RCTs, with a 
number of methodological concerns (e.g., unstructured clinical interview used to diagnose BD, inappropriate 
handling of missing data), failed to support an effect of gabapentin on reducing acute mood symptoms in 
treatment-refractory manic outpatients60 or an admixed sample of medication-free inpatients with BD or unipolar 
depression61. Conversely, results from an additional RCT in euthymic BD supported gabapentin as a prophylactic 
agent62. Important to the proposed study, gabapentin has demonstrated efficacy in treating symptoms that are 
disproportionately present and impairing in individuals with CUD+BD relative to those with CUD or BD alone 
(e.g., anxiety, impulsivity, insomnia)59, 63. Since impulsivity is a core feature of both CUD and BD, it might be 
particularly targeted. In sum, gabapentin has been shown to restore GABA/GLU homeostasis, with treatment 
studies demonstrating efficacy in reducing cannabis use/craving, anxiety, impulsivity, and insomnia in individuals 
with CUD or BD. CUD+BD may be a unique population where gabapentin may have synergistic benefits given 
the magnifying effects of CUD on GABA/GLU function.  
A.4. Conclusion. The proposed 2-week, double-blind, crossover study aims to normalize the dysregulated brain 
GABA/GLU homeostasis characteristic of individuals with CUD and BD using gabapentin, a medication shown 
to restore GABA/GLU homeostasis, and to evaluate medication-related changes in brain activation to cannabis 
and response inhibition (impulsivity) cues, as well as mood and cannabis use, in individuals with CUD+BD. 
B. INNOVATION 
1) No RCTs for CUD+BD have been conducted to date. Positive results from the proposed study may not only 
provide support for the investigation of gabapentin for the treatment of CUD+BD in large RCTs, but may also 
indicate the utility of other interventions affecting GABA/GLU transmission, while simultaneously substantiating 
a tailored imaging platform for testing the promise of such interventions, in individuals with CUD and/or BD.  
2) Although convergent evidence supports GABA/GLU disturbances in CUD and BD, no 1H-MRS studies have 
investigated these disturbances in individuals with co-occurring CUD and BD. The proposed study will be the 
first to investigate whether altering GABA/GLU balance in individuals with CUD+BD results in changes in 
neurobehavioral and clinical variables.  
C. RESEARCH PLAN 
C.1. Preliminary Studies 
C.1.a. Recruitment Experience. Drs. Prisciandaro and 
Tolliver (Co-I) have years of experience of successfully 
recruiting/retaining research participants with SUD+BD 
(AA020842, AA017666)64. Although these studies have 
primarily focused on AUD+BD, 40-50% of participants 
were also diagnosed with CUD. Furthermore, additional 
subjects with CUD+BD, but not AUD, could have been 
available for the proposed study. Finally, Dr. McRae-
Clark (Co-I) has an extensive track record of recruiting 
individuals with CUD to federally funded trials65.  
Figure 1. Sample rBG voxel (center), fitted PRESS GLU 
spectrum (left), fitted MEGA-PRESS GABA spectrum (right). 


C.1.b. 1H-MRS Experience. Drs. Prisciandaro has acquired dorsal ACC (dACC) 1H-MRS data from >200 
subjects to date66, including >100 scans (using the same sequences proposed herein) for an RCT of gabapentin 
in AUD (AA022364, PI: Anton). Data quality has been excellent. We conducted 5 scans of rBG in controls using 
the proposed 1H-MRS protocol. Data quality was uniformly good 
(water linewidth <12 Hz). See Figure 1, above. 
C.1.b. Preliminary data from Dr. Prisciandaro’s K23 study 
demonstrated uniquely low levels of dACC GABA in individuals 
with SUD+BD (n=20) vs. SUD (n=20) or BD (n=19) alone or 
healthy controls (n=19) (Fig 2, left). A similar statistically 
significant interaction was found for dACC glutamate if the 
sample was restricted to individuals who drank/used drugs 
within 2 w of MRI. (All SUD+BD participants met AUD criteria 
within 6 m of MRI and 80% of SUD+BD met lifetime Drug Use 
Disorder criteria; 40% of SUD+BD met past-year CUD criteria).   
C.1.c. Functional 
Magnetic 
Resonance 
Imaging 
(fMRI) 
Exerience. Dr. Squeglia (Co-I) developed a Cannabis Cue 
Reactivity (CCR) fMRI task consisting of cannabis and neutral 
images that is useful for probing the neurobehavioral effects of 
gabapentin: 1) cue reactivity appears to be GABA/GLU mediated9, 
10, 2) cue reactivity/craving are important clinical targets67, and 3) 
reward sensitivity (congruent with the RDoC construct, Approach 
Motivation), arguably best characterized by CCR in CUD+BD68, is 
a core neurobehavioral deficit in both CUD69, 70 and BD71-73. 
Preliminary data, from 41 heavy (M=2x/day) cannabis users (46% women, M age=18.7 ±0.51) demonstrated 
significant activation to cannabis vs. neutral cues (cluster-corrected z > 2.3, p < 0.05) in regions involved in 
reward processing, including bilateral medial prefrontal, striatum, dACC, subcallosal, precuneus, and posterior 
cingulate cortex (Figure 3). As noted in C.2.e (Procedures), the proposed response inhibition (“go no-go”) fMRI 
task, included to better target dACC activation) has been featured in a number of PI-authored publications74, 75.  
C.2. Research Design and Methods. The proposed 2-week, double-blind crossover study will evaluate: a) the 
effects of gabapentin on basal dACC and rBG GABA and GLU concentrations and b) the effects of changes in 
GABA and GLU levels on brain activity to cannabis and response inhibition (impulsivity) cues. The relationship 
between changes in GABA and GLU levels, brain activation to cannabis/response inhibition cues, and clinical 
symptoms (e.g., cannabis use, impulsivity, mood and anxiety) will be explored. Participants will complete two, 1-
week experimental conditions (gabapentin, placebo) in a randomized order. Each condition will consist of a visit 
for assessment and dispensing of medication (Day 1), titration to maximum dose (1200mg/day) (Days 1-5), MRI 
(Day 5), and medication washout (Days 5-7). Spacing of appointments cited throughout the protocol refers to 
ideal conditions which may be minimally deviated from if needed (e.g., +/- 1 day between medication and MRI 
visits, 1 week between conditions). See Figure 4 below for a full study design schematic. 
Figure 3. Robust activation was elicited from 
cannabis, vs. neutral, stimuli in heavy cannabis 
users in reward regions including the medial 
prefrontal cortex, anterior cingulate and striatum. 
Figure 2. Abnormally low dACC GABA in SUD+BD.  


 
C.2.a. Strategies to Ensure a Robust/Unbiased Approach: Explicit inclusion/exclusion criteria; randomization 
of condition order/examination of order effects; placebo control; double blinding; compliance monitoring; use of 
validated MRI, laboratory, and interview/self-report measures/methods; explicit hypotheses and planned 
statistical analyses; power estimates; planned handling of attrition and missing data; and careful consideration 
of potential confounds. Methodology is reported in a detailed and fully transparent manner to support replication. 
C.2.b. Participants. Twenty-three healthy, clinically stable men and women age 18-65 with both CUD and BD 
(or schizoaffective disorder, bipolar type) will be enrolled. Inclusion/exclusion criteria are fully listed below. 
C.2.c. Concomitant Medications. Participants will be required to be taking a stable regimen of ≥1 FDA-
approved mood stabilizing medications for BD; restricting the study to medication-naïve individuals would 
represent a safety hazard and would severely limit recruitment76. To minimize the impact of medications on 
results: 1) individuals taking benzodiazepines > 3x/week will be excluded; positive benzodiazepine UDS at 
baseline, potentially reflecting residual excretion of benzodiazepines with long half-lives (e.g., valium), will be 
further investigated by the PA and/or study physician. Individuals taking atypical antipsychotics will not be 
excluded, as 1H-MRS studies have failed to demonstrate associations between antipsychotic medication load 
and brain GLU/GABA levels77-79, and 2) participants with medication additions, discontinuations, or major dose 
changes ≤ 2 weeks prior to testing will be excluded80. Concomitant medications will be assessed at each visit 
and considered as covariates/moderators in all analyses.  
C.2.d. Recruitment. Recruitment will occur via clinical referral and low-cost advertising (e.g., Craigslist, 
WeSearchTogether.com, ResearchMatch.com) over an 18-month period to reach an enrollment target of 1.25 
CUD+BD participants/month. This project will use ResearchMatch.org, a web-based recruitment tool, to assist 
with enrollment for this study. An e-mail message that, per ResearchMatch’s request, excludes researchers 
direct contact information will be sent to potential study volunteers through this tool.  ResearchMatch’s standard 
notification language that will be received by all ResearchMatch volunteers who may be a match for a given 
study. WeSearchTogether.com will also be utilized in this study which is a web-based recruitment tool for 
individuals that are interested in research related to mood. Referral will prioritize 4 sites: 
• 
The Center for Drug and Alcohol Programs (CDAP) is an inpatient/outpatient SUD treatment facility within 
the MUSC Institute of Psychiatry (IOP). Dr. Tolliver (Co-I) is an attending psychiatrist in the CDAP 
inpatient unit (4N; 0.8 FTE). 40% of participants from our past SUD+BD studies were referred from CDAP.  
• 
The IOP general inpatient unit (3N) has a capacity of 25-30 and regularly refers BD patients to the PI.  
• 
The Ralph H. Johnson VA Medical Center is a tertiary care facility with inpatient, outpatient, and 
residential SUD services from where 20% of Dr. Tolliver’s BD clinical trials subjects were recruited.  
• 
The Charleston Center is an SUD treatment facility located 1 block from MUSC that screens >2,500 
patients/year and provides inpatient, outpatient, and residential treatment. Dr. McRae-Clark (Co-I) has a 
long history of collaboration with Charleston Center through her work with NIDA’s Clinical Trials Network. 
In addition to these methods of recruitment, a chart review will be conducted for research purposes. Potentially 
eligible patients will be identified. The potentially eligible patients in the investigators’ practice will be informed 
about the study as the investigator feels is appropriate. Then potential patients who have agreed to be contacted 
for future research by logging their MUSC Research Permissions preferences in MyChart will be contacted via 
telephone and invited to participate. All other patients will be contacted through their providers to be informed of 


the study if the provider feels it is appropriate. Concerning the RHJVAMC, we will seek separate approval through 
the VAMC to post and distribute VA-approved study fliers.   
 
 
 
Table 1. Schedule of events by study visit 
Study Visit 
Visit 1 
Evaluation 
Visit 2 
Med Disp 
Visit 3 
MRI 
Visit 4 
Med Disp 
Visit 5 
MRI 
Clinician and PA 
Informed Consent* / HIPAA* / 
BrAC contract* 
X 
 
 
 
 
SCID-5 (Mood/Substance)* 
X 
 
 
 
 
TLFB* (90 day at V1) 
X 
X 
X 
X 
X 
YMRS* / MADRS* / C-SSRS*  
X 
X 
X 
X 
X 
BDRS / BR 
 
X 
X 
 
X 
Observe Dose (note time) 
 
X 
X 
X 
X 
H&P* / Metal Screen* 
X 
 
 
 
 
AEs / Vitals 
 
X 
X 
X 
X 
Self-Report 
Demographics / Family history 
X 
 
 
 
 
BDI* / PSQI* / BAI*  
X 
 
 
 
 
BIS-11 / SPSRQ / AUDIT / 
ASRS / WHODAS / DSM-5 
PID5/PQ  
X 
 
 
 
 
BDI PW / PSQI PW / BAI PW 
(PW=Past Week) 
 
X 
X 
 
X 
FTND / ASRM / MCQ / CWS 
X 
X 
X 
 
X 
Actiwatch Data Download 
 
 
X 
X 
X 
Urge to use MJ [1-10] 
(PRE/POST MRI) 
 
 
 
 
X 
Computer Tasks 
STOP-IT  
X 
 
X 
 
X 
Delay Disc  
X 
 
 
 
 
GoGoNoGo Practice 
 
 
X 
 
 
CNL Labs 
CMP* / CBC* / DNA* 
X 
 
 
 
 
%dCDT 
 
X 
 
 
 
Gabapentin level 
 
 
X 
 
X 
EtG 
 
X 
X 
 
X 
Riboflavin 
 
X 
X 
 
X 
Cannabinoids/Creatinine Levels 
 
X 
X 
X 
X 
In-House Labs 
Collect urine specimen* / UDS* 
X 
X 
X 
X 
X 
Breathalyzer* 
X 
X 
X 
X 
X 
Pregnancy Test* 
X 
 
X 
 
X 
Saliva drug screen 
 
X 
X 
 
X 
Note: “*” Indicates assessments that must be done at Visit 1. Non-starred assessments at Visit 1 can be 
completed at Visit 2 if needed.  


C.2.e. Procedures. See Table 1. 
Eligibility and Medical / Psychiatric Assessment (Visit 1). Following brief screening over the phone or at a 
referral site, potential participants will be scheduled for formal screening at an Addiction Sciences Division 
research clinic. They will read and sign an IRB-approved informed consent (IC) document and will then be 
assessed for eligibility using the Structured Clinical Interview for DSM-V81. Trait impulsivity will be assessed via 
the Barratt Impulsiveness Scale (BIS-11)82. Past 90 day drug/alcohol use will be assessed with the Timeline 
Followback (TLFB)83. Cannabis use will be recorded in times used/day as well as quantity (e.g., grams, number 
of joints) to standardize for different types of use. Participants will be asked to quantify cannabis use by weighing 
out amounts of an inert surrogate and reporting on that amount’s potency through dollar value estimates. Recent 
methods of use will then be quantified using this system (bowls, bongs, blunts, ingestion)84. Cannabis craving 
will be measured using the 12-item, Marijuana Craving Questionnaire (MCQ)85. Past 24-hour withdrawal 
symptoms will be assessed using the Cannabis Withdrawal Scale (CWS)86. Mood symptoms will be assessed 
using the clinician-administered Young Mania Rating Scale (YMRS)87 and Montgomery-Asberg Depression 
Rating Scale (MADRS)88, 89, supplemented with items from the Bech-Rafaelsen Mania Rating Scale (Bech et al., 
1978) and Bipolar Depression Rating Scale (Berk et al., 2007), along with the self-report Beck Depression 
Inventory-II (BDI-II)89, Beck Anxiety Inventory (BAI)90, and Altman Self Rating Mania Scale (ASRM; Altman et 
al., 1997). Sleep will be assessed using the Pittsburgh Sleep Quality Index (PSQI)91. Personality pathology 
(Personality Inventory for DSM-5; PID-5; Suzuki et al., 2015), ADHD symptoms (Adult ADHD Self-Report Scale; 
ASRS; Kessler et al., 2005), functional impairment (WHO Disability Assessment Scale; WHODAS; WHO, 2010), 
Sensitivity to Punishment and Sensitivity to Reward (SPSRQ; Torrubia et al., 2001), alcohol use severity (AUDIT; 
Saunders et al., 1993), and family psychiatric history (Sachs et al., 2003) will also be assessed. A 
breathalyzer/intoxication policy will be provided to each participant to indicate steps taken by clinical staff if the 
participant’s reading is over 0.08. Given that GABA/GLU dysfunction in BD is evident across mood states25-31, 
participants reporting mood symptoms will not be excluded in order to maximize feasibility and generalizability 
to clinical populations. Safety assessments, including the Columbia Suicide Severity Rating Scale (C-SSRS)92, 
will be conducted at each visit to assess for symptomatology requiring medication adjustment or hospitalization 
(see Human Subjects for full safety plan). MRI safety will also be assessed. Potential participants will undergo a 
full medical history and physical exam and will provide samples for blood chemistries (General Health Panel 
[CMP], Complete Blood Count [CBC]) and genetic testing. Qiagen DNA extraction kits are used to extract DNA 
from whole blood by a dedicated genetic technician in Dr. Anton's lab, tested for DNA purity, and used in Taqman 
PCR analysis with specific probes and primers purchased from Life Science Technologies using a Step One 
analyzer (Applied Biosystems). Dr. Anton's KO5 funding allowed him to become proficient in this type of analysis 
and he has genotyped hundreds of samples with various SNP’s and VNTR’s including the glutamate and GABA 
genes of interest (see background section). Qualitative drug screens will be performed using the Discover 12 
Panel Cup, an in vitro diagnostic test for the detection of drug/drug metabolite in urine. Urine will also be tested 
for Ethyl Glucuronide (EtG) to evaluate recent alcohol drinking. Participants will provide a saliva sample to test 
for recent cannabis use using SalivaConfirm (Confirm Biosciences, Inc). Semi-quantitative urine cannabinoid 
screens (detection cut-off=20.00 ng/ml) will be performed, and normalized to creatinine93, using the Architech® 
system from Abbott Laboratories. Female participants will take pregnancy tests. Finally, eligible participants will 
complete two brief (<10m) computer tasks to measure delay discounting (Green et al., 1994) and stop signal 
reaction time (STOPIT; Verbruggen et al., 2008).  
Inclusion Criteria: 1) Subjects must meet DSM-5 criteria for current CUD and provide a positive urine cannabinoid 
screen at baseline. They must additionally self-report cannabis use within the past 30 days and report using 
more days than not in the month preceding abstinence. 2) Subjects must meet DSM-5 criteria for bipolar disorder 
(or schizoaffective disorder, bipolar type) and must be prescribed daily use of ≥1 mood stabilizing medication 
(i.e., lithium, atypical antipsychotic, divalproex sodium / valproate, carbamazepine, lamotrigine). 3) Women of 
childbearing potential must utilize effective birth control. 
Exclusion Criteria: 1) History of significant hematological, endocrine, cardiovascular, pulmonary, renal, 
gastrointestinal, or neurological disease. 2) History of psychotic disorder (e.g., Schizophrenia). 3) Current 
suicidal or homicidal ideation. 4.) Subjects meeting DSM-5 criteria for moderate/severe SUD (other than nicotine 
or cannabis) within the past month. 5) Concomitant use of benzodiazepines (>3x/week), or electroconvulsive 
therapy in the past month. 6.) History of clinically significant brain injury. 7.) Presence of non-MRI safe materials 
or significant claustrophobia. 8.) Use of medications hazardous if taken with gabapentin. 9.) History of allergic 
reaction to gabapentin. 10.) Plasma creatinine levels > 2x the normal range. 11.) Clinically significant mania 
(YMRS > 25) or severe depression (MADRS > 35), to ensure safety and decrease between-subjects variability. 
Medication Dispensing (Visits 2, 4). Participants will complete any assessments not required for 


inclusion/exclusion determination and not completed at Visit 1 at Visit 2. At Visit 2, participants will be asked to 
wear an actigraphy watch (Actiwatch Spectrum Plus, Philips Respironics) on their non-dominant wrist for the 
remainder of the study. They will be instructed on its use (e.g., not to take it off when showering) and asked to 
keep a brief actigraph log (e.g., sleep and wake times) delivered daily via text/e-mail using REDCap. On day 1 
of each condition, mood symptoms (YMRS, MADRS, C-SSRS) and alcohol/drug consumption (TLFB, UDS) will 
be assessed. Medications will be packaged and dispensed by the MUSC Investigational Drug Service (IDS). IDS 
will oversee blinding procedures for the study and maintain treatment assignment records. Medication will be 
over-encapsulated with riboflavin (25mg/capsule), for urinary detection by fluorescence spectroscopy at each 
MRI, with each capsule containing either 300mg of gabapentin or matching placebo dispensed in blister packs. 
At each Dispensing visit, participants will take their first dose in front of study staff to ensure compliance. They 
will receive detailed instructions regarding the dosing schedule for days 1-5 of the condition (See Figure 4). 
Gabapentin has an elimination half-life of 6-7 hours94. Participants should reach steady state concentrations of 
the maximal dose (1200mg) well before the MRI visit95. Twice daily dosing will be used to maximize compliance. 
The proposed titration schedule is consistent with our experience with gabapentin for AUD96-98, gabapentin 
studies in CUD57, and our clinical experience with dual diagnosis patients. Unused medications will be returned 
for pill counts. Gabapentin blood levels will be obtained for all participants, in house, using a validated 
immunoassay99. Medication adherence will be evaluated as a covariate.  Due to flexibility in scheduling (+/- 1 
day for the MRI visit), extra medication will be provided for each participant and labeled as such to ensure 
participants have the correct number of doses.  
MRI (Visits 3, 5). MRI visits will take place on day 5 of each condition. Participants will be asked to abstain from 
drugs/alcohol ≥12 hours prior to MRI. They will take their final dose of medication in front of study staff, 1 h prior 
to MRI, to ensure compliance. Participants who smoke will be allowed to have their last cigarette immediately 
prior to their final medication dose. Mood symptoms (YMRS, MADRS, C-SSRS, BDI, BAI, ASRM, PSQI), 
alcohol/drug/tobacco consumption (TLFB, UDS, FTND, EtG, Saliva), cannabis withdrawal (CWS), and cravings 
(MCQ) will be assessed. Participants will provide a urine and blood sample to test for gabapentin levels, 
riboflavin, liver function, and alcohol/drug consumption. Following structural and 1H-MRS scanning, participants 
will complete the CCR and go no-go fMRI tasks in counterbalanced order (see below) with the Natural Rewards 
Task at the end. fMRI tasks will be conducted while acquiring BOLD weighted transverse scans using a gradient-
echo, echo-planar imaging (EPI) sequence: TR/TE=2200/35 ms; flip angle=90°; field of view=220x220 mm; voxel 
size=3.00x3.00 mm; 37 contiguous 3-mm-thick slices. Total scan time is approximately 75 m in a Siemens 3.0T 
Prisma (32-channel head coil). Participants will discontinue study medication following each MRI and will remain 
off study medication on days 6-7 of the condition. Given that the last gabapentin dose will be taken in the morning 
of day 5, this will provide approximately 11 half-lives of elimination prior to the start of the next condition. 
Crossover studies employing up to 3x the proposed dose of gabapentin have demonstrated an absence of 
carryover effects on clinical outcomes given the same100 or fewer101 days of washout as proposed herein. 
Potential carryover effects will be carefully examined using the proposed analytic design. Outside of the scanner, 
participants will complete the STOP-IT task. Within approximately 72 hours of day 7 of the final study condition, 
participants will be contacted by clinically-trained study staff to discuss adverse events, alcohol and drug 
consumption, and mood stability since discontinuing study medication.  
1H-MRS Acquisition. A structural scan will be taken for 1H-MRS voxel placement and tissue segmentation (256 
sagittal slices; 1mm thick/50% gap). dACC and rBG contain different concentrations of GABA102 and form an 
important fronto-striatal reward circuit103. We will acquire data from both regions to evaluate whether gabapentin 
effects, as well as associations between GABA and cannabis/response inhibition cue-reactivity, are region 
specific. The dACC voxel will be placed on midsagittal T1-weighted images, posterior to the genu of the corpus 
callosum, with the ventral edge aligned with the dorsal edge of the callosum104. An rBG voxel will be placed on 
an axial T1-weighted slice about 1 cm above the genu, between the Sylvian fissure and the lateral ventricles 
including corpus striatum105. Each voxel will be 2.5x2.5x3 cm3 to ensure adequate signal to noise. Following 
placement of 6 saturation bands at least 1 cm away from the voxel faces and auto-shimming via FASTESTMAP, 
single-voxel water-suppressed 1H-MRS spectra will be acquired using a MEGA-PRESS sequence (TR=2000ms; 
TE=68ms; number of averages=300) with symmetric editing pulse frequencies (1.9 ppm and 1.5 ppm) for 
macromolecule suppression106 and a PRESS sequence maximally sensitive to GLU (TR=2000ms; TE=40ms; 
number of averages=128)107. Unsuppressed water spectra will be acquired for each sequence.  
Cannabis Cue Reactivity. During the CCR fMRI task, participants are shown pseudorandomly interspersed 
cannabis (cannabis plant, paraphernalia) and neutral (e.g., pine cone, trumpet) images, visual control (blurred) 
images, and a fixation cross. The cannabis stimuli were matched by color, hue, and complexity. Stimuli are 
presented in six 120 s epochs, each consisting of four blocks of an image type. Participants rate their “urge to 


use marijuana” after each block, 0 (“none”) to 4 (“severe”), using a handpad. See Figure 3 for preliminary data. 
Response Inhibition (Impulsivity). The “go no-go,” response inhibition, fMRI task consists of 20 blocks, lasting 
26.25 s each; 10 go no-go blocks alternate with 10 fixation blocks, in which a cross is presented for the duration 
of the block. During go no-go blocks, participants are presented with 21 letters, one at a time, for 250 ms each, 
followed by 1 s interstimulus intervals (black screen). They are instructed to press a button on their handpad as 
soon as they see a letter other than “X,” but to withhold response if they see the letter “X,” which is presented 
20% of the time. Presentation order of letters is randomized to remove confounding effects due to the overlap of 
hemodynamic responses. This task was featured in several publications authored by the PI74, 75.  
Natural Rewards Task. The natural rewards paradigm, recently developed by Drs. Mellick, Prisciandaro, and 
McTeague, contains pictures of social rewards (romance, family, children and babies), food rewards, and 
nonsocial and household object control images; all of which were selected from the International Affective 
Picture System (IAPS; Lang et al., 2005) and matched in color and hue. Chosen pictures were carefully 
selected based on prior fMRI research with natural rewards and alcohol cues (e.g., Garavan et al., 2000; 
Tomasi et al., 2015; Ihssen et al., 2010). These studies were most informative to the selection of food and 
household object control images. As social rewards have yet to be examined as they are in this task, a bottom-
up approach was taken in picture selection. Best practices as outlined in the IAPS technical manual were 
adhered to when forming each picture category (Lang et al., 1997). First, the entire IAPS catalog, was 
reviewed and candidate pictures were identified based on content. Pictures were then excluded for 
composition, color, contrast, hue, and cropping. Those which may be interpreted as ambiguous by participants 
were also excluded. Next, normative valence (unpleasant to pleasant) and intensity (calm to excited) ratings, 
provided by IAPS developers, were reviewed with the goal of selecting social and food pictures high in valence 
and intensity, and nonsocial and household object control images of neutral valence and low intensity. Specific 
to the nonsocial control category, pictures depicting people looking towards the viewer were excluded to avoid 
activation in regions associated with facial recognition (e.g., fusiform gyrus; Haxby et al., 2000). 
C.2.f. Statistical Considerations 
Sample Size Determination. Data from an ongoing investigation of gabapentin for AUD (n=21), where 
participants are scanned prior to, and 2 weeks following, initiation of gabapentin treatment or placebo, were used 
to inform power calculations for the proposed study; as the study remains blinded, estimates of variability and 
correlation between scan 1 and 2 GABA concentrations were taken from the combined sample. An estimate of 
anticipated dropout was derived from Dr. Tolliver’s trial of lamotrigine in AUD+BD, where 20% of participants 
dropped out by week 3. According to these estimates, with 18 completers (23 enrolled with 20% dropout), the 
proposed study would have >80% power to detect a ≥25% increase in GABA given a ≥0.60 correlation of GABA 
estimates across scans (observed r =0.72). Gabapentin studies have found 25-50% increases in GABA45, 46, 48. 
1H-MRS/fMRI Processing. MEGA-PRESS (GABA) data will be analyzed using the Gannet MATLAB toolbox108 
and PRESS (GLU) data using LCModel 6.3109. Metabolites with fitting uncertainties <20% will be retained. Within-
voxel tissue fractions of gray and white matter and CSF will be calculated based on automated segmentation in 
Statistical Parametric Mapping 12 (SPM12, Wellcome Department of Cognitive Neurology)110. Metabolite 
concentrations will be normalized to the unsuppressed water signal and corrected for within-voxel CSF fraction. 
fMRI analysis will be completed in SPM12. Standard fMRI preprocessing including realignment, normalization, 
and smoothing will be performed. Preprocessed data will be analyzed within a general linear model mixed effects 
framework. For the CCR task, the main contrast of interest will be the cannabis vs. neutral images contrast. For 
the go no-go task, the main contrast of interest will be the no-go vs. go trial contrast. Following 1st-level analysis, 
subject-specific spatially-normalized contrast maps will be entered into 2nd-level, random-effects analyses. 
Condition parameter maps will be thresholded at p<0.05, corrected for multiple comparisons.  
Data Analysis. Generalized linear mixed effects models will be employed to assess the effect of gabapentin on 
dACC and rBG GABA levels (Hypothesis 1). As detailed above, whole-brain random-effects analyses will be 
conducted to assess the direct effect of gabapentin, as well as the direct effect of gabapentin-induced changes 
in GABA, on brain activation to cannabis and response inhibition (impulsivity) cues (Hypothesis 2). These 
analyses will be supplemented with a region of interest approach (extracting % signal change from participants’ 
1H-MRS voxels) using the MarsBaR SPM toolbox. Primary models for Hypotheses 1 and 2 will contain the main 
effect of treatment, period (scan 1 v. scan 2), and sequence (gabapentin 1st v. placebo 1st) to ensure the 
crossover design and washout were successful. All models will be re-estimated with GLU levels entered in place 
of GABA (Exploratory Hypothesis 1). To synthesize hypotheses 1-2, mediation models will be estimated in which 
metabolite levels are posited as mediators of the association between medication treatment and brain activity to 


cannabis and response inhibition cues111. We will employ previously successful methods to minimize attrition, 
but mixed effects models can be used to provide valid estimates assuming data are missing at random112.  
Exploratory/covariate analyses. 1) Mood and substance use: It is likely that mood and substance use will vary 
within individuals, across visits. We will examine associations between mood (YMRS, MADRS), substance use 
(TLFB, UDS, EtG, Saliva), and GABA and GLU levels, and will evaluate mood and substance use variables as 
covariates in all analyses. Potential medication-related changes in anxiety (BAI), sleep (PSQI), and impulsivity 
will also be explored (Exploratory Hypothesis 2). 2) Age, sex, smoking status, AUD, anxiety disorder, concomitant 
medications. Age, sex, and smoking status have been associated with GABA and GLU levels in the extant 
literature113-115. Co-occurring anxiety disorders and AUD are very common in individuals with BD116, 117 and have 
been associated with GABA/GLU dysregulation104, 118, 119. Participants with anxiety and AUD will not be excluded 
to enhance feasibility/clinical generalization. Given the within-subjects design of the study, between-subjects 
variables are not potential confounders; nonetheless, we will consider these variables as moderators in all 
analyses. Potential indications of sex differences will be considered in future, larger studies. 
C.2.g. Potential Limitations. 1) Previous studies that have demonstrated gabapentin-induced increases in brain 
GABA have been conducted in controls and epileptics. Whether these findings will generalize to CUD+BD is 
unknown. 2) Mood and substance use are potential confounders of condition comparisons as they can change 
over the course of the study in a given individual. Their impact on study outcomes will be carefully examined and 
they will be evaluated as potential covariates in all models. 3) A potential challenge to completing the study will 
be recruiting/retaining a sufficient number of CUD+BD participants. If recruitment goals are consistently not met, 
the study team will meet to discuss strategies for meeting goals without compromising the integrity of the study.  
C.2.h. Future Directions. Positive results may support investigation of gabapentin for the treatment of CUD+BD 
in large RCTs. The proposed study may also provide successful demonstration of a multimodal imaging platform 
for evaluating the promise of other GABA/GLU drugs for CUD and/or BD. This study will also add to the literature 
on associations between GABA/GLU and RDoC constructs central to CUD/BD (impulsivity and cue reactivity).  
C.2.i. Timeline. Purchasing, setup, and regulatory approval will be completed within the first 3 months of Yr 01. 
11-12 participants will be recruited/year. Analysis and manuscript submission will begin in the 2nd half of Yr 02. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 


 
 
 
 
Protection of Human Subjects 
1. Risk to the Subjects 
a. Human Subject Involvement and Characteristics. A total of 23 individuals in stable medical condition will 
be enrolled in the study. Women and minorities will be recruited for this study. Children and adolescents under 
the age of 18 will not be enrolled.  
Inclusion Criteria:  
1. Age 18-65 
2. Meet DSM-5 criteria for current CUD, provide a positive urine cannabinoid screen at baseline, self-report 
cannabis use within the past 30 days and using cannabis more days than not in the month preceding 
abstinence.  
3. Meet DSM-5 criteria for bipolar I or II disorder (BD) or schizoaffective disorder, bipolar type.  
4. Able to provide informed consent and read, understand, and accurately complete assessment instruments  
5. Willing to commit to medication treatment and follow-up assessments 
6. Prescribed daily use of at least one mood stabilizing medication (i.e., lithium, atypical antipsychotic agents, 
divalproex sodium / valproate, lamotrigine, carbamazepine) 
Exclusion Criteria: 
1. A primary psychiatric diagnosis other than BD (e.g., Schizophrenia) 
2. Meet DSM-5 criteria for moderate or severe substance use disorder (other than nicotine or cannabis) within 
the past month.  
3. Any uncontrolled neurologic condition (e.g., epilepsy) that could confound the results of the study 
4. Any history of clinically significant brain injury 
5. Any history of mental retardation, dementia, or electroconvulsive therapy in the past month 
6. Any uncontrolled medical condition that may adversely affect the conduct of the study or jeopardize the safety 
of the subject 
7. Hepatocellular disease as indicated by plasma levels of liver transaminases (aspartate transaminase, alanine 
transaminase) greater than 3 times the normal range 
8. Reduction in creatinine clearance greater than 2 times the normal range 
9. Concomitant use of medications that could interfere with glutamatergic/GABAergic transmission (e.g., 
benzodiazepines > 3x/week, ceftriaxone, riluzole, memantine, ketamine, topiramate, vigabatrin), due to 
potential confounding effects 
10. Azelastine, orphenadrine, oxomemazine, paraldehyde, and thalidomide are contraindicated in patients 
taking gabapentin; as such, individuals taking these medications will be excluded 
11. Women of childbearing potential who are pregnant, lactating, or refuse adequate forms of contraception 
12. Current suicidal or homicidal risk 
13. Baseline scores greater than 35 on the Montgomery-Asberg Depression Rating Scale or greater than 25 on 
the Young Mania Rating Scale 
14. Has taken gabapentin in the last 2-weeks or experienced adverse effects/allergic reaction (e.g., angioedema) 
from it at any time 
15. Significant claustrophobia and/or past negative experiences with MRI 
16. Presence of non-MRI safe materials in the body (e.g., ferrous metal implants, pacemaker) 
b. Source of Materials. Data collected from participants will include breathalyzer readings, urine drug screens, 
urine biomarkers (e.g., riboflavin, ethyl glucuronide), blood chemistries, structural, functional, and neurochemical 
MRI brain images, and interviews and self-reports regarding substance use, psychiatric diagnoses, concomitant 
medications, and adverse events. To ensure confidentiality, all participant data will be number-coded, and only 
the investigators will have access to the master list of codes. A federal Certificate of Confidentiality, protecting 
participants against disclosure of sensitive information (e.g., drug use), will be obtained for the study.   
c. Compensation. To maximize participant retention, contingency management will be applied to participant 
compensation such that participants will be compensated significantly more for each subsequent MRI visit they 


attend (i.e., scan 1 = $100, scan 2 = $150), and participants will be given an additional $50 bonus for completing 
both MRI visits without rescheduling and for returning their actigraphy watch. Participants will be compensated 
$10/hour (rounded to the nearest half-hour) during the diagnostic visit if screened out during this time. 
Participants will be compensation $50 for completing the full initial psychiatric and medical evaluation 
appointment. Finally, participants will be compensated $30 for each additional non-MRI appointment (i.e., 2 
total). Following the initial appointment, participants will be compensated weekly, at the end of each MRI session; 
$50 of each week’s compensation will be contingent on them returning their actigraphy watch to the appointment. 
Total compensation will thus be $410 per participant. In our experience, this level of compensation is fair for the 
time commitment required without unduly coercing participants to enroll in the study despite potential concerns. 
d. Potential Risks 
1. Medication side effects. Gabapentin is generally well-tolerated, with sedation and dizziness being the most 
commonly reported side effects96, 97. Although the FDA has issued a class warning for antiepileptic drugs and 
suicidal thoughts and behavior, available data do not support an association between gabapentin, 
specifically, and increased suicidal ideation or behavior in individuals with BD or other psychiatric 
populations97, 98. The proposed study will minimize potential medication-related risks by implementing low 
starting doses and titration of study medications and will carefully monitor potential medication-related risks 
via biweekly scheduled visits and assessment of adverse events (including assessment of suicidal ideation 
and behavior at each and every study visit). The study physician will determine if the participant should be 
discontinued from the medication due to adverse drug reactions and will treat clinically as needed. Any 
confirmed incidence of serious adverse events that are deemed probably or definitely due to the study 
medication will result in immediate discontinuation of the study medication and follow-up assessments will 
be conducted until resolution. Subjects will be referred for treatment as necessary.  
2. Drug interactions. Azelastine, orphenadrine, oxomemazine, paraldehyde, and thalidomide are 
contraindicated in patients taking gabapentin; as such, individuals taking these medications will be excluded. 
As noted earlier, participants will be required to be taking a stable pre-existing regimen of at least one FDA-
approved mood stabilizing medication treatment for BD. There are no known serious drug interactions with 
gabapentin and mood-stabilizing medications. 
3. MRI-related risks. Individuals with non-MRI-safe medical implants or ferrous objects would be at risk for 
injury, if such individuals were allowed to enter the MRI scanner. Several precautions will be taken to ensure 
that individuals with ferrous implants or objects are not allowed to enter the MRI scanner. First, all potential 
participants will meet with a study physician to discuss any possible history of ferrous implants or other MRI-
unsafe objects. Participants with any suspected history of ferrous implants or exposure to shrapnel will be 
excluded from the study. Second, participants who are deemed MRI-safe by the study physician will be 
screened for metal objects at the Center for Biomedical Imaging (CBI) using a handheld metal detector and 
a second metal detector built into the threshold of the doorway to the scanner. Participants who screen 
positive for metal will be asked to remove all metal objects from their person and will be rescreened. If 
participants continue to screen positive for metal after removing all metal objects from their person, they will 
be excluded from the study. Although not dangerous, participants who are claustrophobic could experience 
significant discomfort in the MRI scanner. As such, all participants will be assessed in terms of claustrophobia 
as well as past experience with MRI. Additionally, all participants will be entered into a “mock scanner” at the 
CBI human imaging center, which features the same dimensions of the real MRI scanner but without any of 
the internal machinery. Participants who report claustrophobia, past negative experience with MRI, or 
signification discomfort in the mock scanner will be excluded from participation. These procedures have been 
successfully used by our staff in previous and ongoing research studies of similar participant populations. 
For those participants allowed to participate in the MRI study, if abnormalities in collected brain images are 
found, participants will immediately be referred to an appropriate clinical care provider. 
4. Cue-elicited cannabis craving. It is possible that the cannabis cue exposure functional MRI paradigm could 
induce cannabis craving. Participants will be asked to rate their craving from one to ten both immediately 
preceding and following the neuroimaging protocol. Post-scan craving ratings twenty percent above baseline 
will require study approved clinicians to come and speak with the patient before they are discharged. Should 
any craving fail to subside within 3-4 hours, participants will be provided with counseling by clinicians; 
appropriate referrals will be made as needed. These procedures have been successfully used by our staff in 
previous and ongoing research studies of similar participant populations. 
5. Cannabis consumption and withdrawal. Subjects will not be required to establish abstinence at any time 
during the study, however, they may voluntarily attempt abstinence during the course of the study. 
Participants who voluntarily attempt abstinence may experience cannabis withdrawal symptoms. Study 


participants will be monitored for cannabis withdrawal symptoms. Conversely, participants may continue to 
consume cannabis. The risks of continued cannabis use may include but are not limited to psychiatric 
morbidity, increased risk of traumatic injury, and other medical consequences. If in the PI’s opinion a 
participant has significant worsening of cannabis use problems or consumption of cannabis as a result of 
participating in the study, the subject will be withdrawn from the study and appropriately referred.  
6. Mood destabilization. Exacerbation of depressive or manic symptoms during the course of the study is a risk 
for all subjects regardless of treatment condition. We will minimize this risk by assessing mood symptoms, 
including suicidal ideation and behavior using the Columbia Suicide Severity Rating Scale (C-SSRS), at each 
and every study visit. Participants experiencing sufficient deterioration of mood stability to result in clinically 
significant impairment in functional capacity will be appropriately referred. Any subject exhibiting mood 
destabilization that is sufficient to pose an imminent danger to self or others will be hospitalized immediately 
and removed from the study.  
 
2. Adequacy of Protection Against Risks 
a. Recruitment and Informed Consent. Recruitment will occur by clinical referral, response to advertisements 
and flyers, and chart review. The principal investigator, the study coordinator, co-investigators with completed 
masters-or-higher-level clinical training will obtain informed consent. At the screening visit, potential participants 
will be provided a copy of the IRB-approved consent document to review. After providing the participant with 
time to read the consent, the principal investigator, the study coordinator, co-investigators with completed 
masters-or-higher-level clinical training will review the consent document page by page with the participant and 
answer any questions. Only then will the participant be asked to sign the consent document. Participants will be 
given a copy of the signed consent document. The entire informed consent process will be documented in the 
research progress notes. The signed, original consent document will be maintained in the participant source 
record with a copy of the consent binder located at the Addiction Sciences Division, Department of Psychiatry 
and Behavioral Sciences, Medical University of South Carolina.  
b. Safety Assessments. At every visit, clinically-trained study staff will evaluate subjects’ manic and/or 
depressive symptoms, including suicidal ideation. Mood symptoms will also be quantified using standardized 
instruments including MADRS, YMRS, BDI-II, and BAI. Adverse events will be assessed at every study visit.  
c. Protection Against Risk. 
Psychiatric Risks. The investigative team has a great deal of experience working with the study population and 
have the resources to make appropriate referrals as needed. Psychiatric symptoms will be assessed on a 
biweekly basis by standardized assessments and by clinical interview. Participants scoring >4 on the suicide 
item (item 4) of the MADRS; endorsing items 4 (“Have you had these [suicidal] thoughts and some intention of 
acting on them?”), 5 (“Have you started to work out or worked out the details of how to kill yourself? Do you 
intend to carry out this plan?”), or 6 (“Have you done anything, started to do anything, or prepared to do anything 
to end your life?”) on the C-SSRS, or otherwise exhibiting potentially life-threatening decompensation in mood 
or other psychiatric symptoms at any study visit will be removed from the study and referred for outpatient or 
inpatient treatment as necessary.  
Medical Risks. Gabapentin is excreted by a renal route. A blood chemistry panel will be performed and reviewed 
by the study physician prior to beginning the study medication. Participants with clinically significant renal, or 
hepatic (transaminases elevated > 3 times normal), insufficiency will not be eligible to participate in the study. 
Subjects will be referred for treatment as necessary.  
MRI Risks. The investigative team has a great deal of experience with human MRI research and Dr. Prisciandaro 
is a core faculty member of the CBI at MUSC. MRI safety and comfort will be assessed at baseline and at each 
MRI visit. Participants with non-MRI-safe medical implants or ferrous objects will be excluded from participation 
as will individuals evidencing significant discomfort with MRI.  
Pregnancy. Gabapentin is rated as a Category C medication in terms of pregnancy. Because there are no 
adequate controlled studies of gabapentin in pregnant women, it is unknown whether the drug can cause fetal 
harm or affect reproductive capacity in humans. Therefore, women of childbearing potential must agree to 
pregnancy testing and use of adequate contraception in order to be eligible to participate in the study. Females 
will be given a urinary pregnancy test at the screening visit and weekly thereafter. Any female participant who 
becomes pregnant during the study will be discontinued from the study medication and removed from study 
participation. For all included females of childbearing potential, current forms of birth control and date of last 
menstruation will be assessed at each study visit.  


Confidentiality. Records with identifying information (e.g., consent documents) will be stored in a locked file. All 
other non-MRI participant data will be collected via direct data capture (REDCap); MRI data will be automatically 
transferred to Linux-based servers managed by CBI. Both MRI and non-MRI data will be stored in restricted 
access directories on password-protected, encrypted servers managed by CBI and the Department of Psychiatry 
and Behavioral Sciences at MUSC. Participants will be given an ID number for all MRI and non-MRI data files. 
The master list of codes will be accessible only to the investigators, and will be stored in a locked office. As noted 
above, a federal Certificate of Confidentiality, protecting participants against disclosure of sensitive information 
(e.g., drug use), will be obtained prior to study initiation.   
Emergencies. All study participants will be instructed how to access the 24-hour on-call system available at the 
Medical University of South Carolina. In the event that a participant experiences an adverse event after hours, 
s/he will be instructed to access the 24-hour on-call service. If it is determined that the participant needs 
immediate help, the participant may be advised to immediately go to the emergency room. In that event, proper 
medical treatment will be administered, per ER procedures. Dr. Prisciandaro and Dr. Tolliver will be available by 
pager/cell as necessary. The Investigational Drug Service (IDS) will be available 24 hours/day, 7 days/week for 
emergency identification of treatment group assignment and unblinding as necessary. 
Substance Abuse Treatment. Subjects may receive additional non-pharmacologic substance abuse treatment 
during study participation. Attendance at group-based recovery activities (e.g., Narcotics Anonymous) will be 
encouraged and monitored.  
 
3. Potential Benefits of the Proposed Research to the Subjects and Others  
Benefits to the subjects include medical and psychiatric assessments provided at no cost. Subjects may benefit 
by reduction of cannabis consumption as an effect of active treatment or through nonspecific effects of study 
participation (increased awareness of cannabis consumption, frequent interactions with study personnel, etc.), 
although this is not guaranteed for any given subject. Other individuals with comorbid CUD and BD are likely to 
benefit by the knowledge gained from the study as it may help guide future treatments.  
 
4. Importance of the Knowledge to Be Gained 
There is a six-fold increase in the prevalence of CUD in individuals with BD relative to the general population; 
this common comorbidity is associated with substantially elevated negative outcomes, including treatment 
resistance. Treatment research for co-occurring CUD and BD is extremely limited, with no randomized trials for 
CUD+BD conducted to date. The proposed study will evaluate the ability of a medication (i.e., gabapentin) that 
has been shown to increase cortical GABA levels in past research to manipulate a neurochemical dysfunction 
characteristic of individuals with CUD+BD (i.e., dysregulated brain GABA/glutamate homeostasis). Positive 
results may support investigation of gabapentin for the treatment of CUD+BD in large-scale, randomized clinical 
trials. Furthermore, the proposed study may provide successful demonstration of a neurobehavioral, multimodal 
neuroimaging platform for evaluating the potential promise of GABAergic drugs for CUD and/or BD, as well as 
other conditions marked by GABA/glutamate dysfunction. The proposed investigation's minimal risks are 
reasonable in relation to the importance of the knowledge to be gained from the investigation. 
 
5.   Clinicaltrials.gov Requirements 
In accordance with Public Law 110-85, this project will be registered at the ClinicalTrials.gov Protocol 
Registration System Information Website prior to study initiation. 
 
 
 
 
 
 
 
 
 


 
 
 
 
 
 
 
Data and Safety Monitoring Plan 
This section is based on the recommendations in NIDA’s “Guidelines for Developing a Data and Safety 
Monitoring Plan”.  
1) Summary of the Protocol.   
This application proposes to investigate the effects of gabapentin on brain GABA and glutamate concentrations, 
a neurobehavioral measure of cannabis cue-reactivity, and mood and cannabis use in individuals with co-
occurring cannabis use disorder and bipolar disorder. The primary outcomes of interest are brain GABA and 
glutamate levels and a neurobehavioral measures of cannabis cue-reactivity. Inclusion/exclusion criteria are 
outlined in Protection of Human Subjects. Power calculations and sample sizes are detailed in the Sample Size 
Determination section of the Research Strategy.  
2) Trial Management.   
The study will be managed from the Addiction Sciences Division within the Department of Psychiatry and 
Behavioral Sciences at the Medical University of South Carolina (MUSC). The target population is described 
above in the inclusion/exclusion criteria. 
3) Data Management and Analysis. 
Non-MRI data will be collected via direct data capture (REDCap) on tablet devices and stored on MUSC 
centralized secured, backed-up servers. MRI data will be automatically transferred to Linux-based servers 
managed by the Center for Biomedical Imaging (CBI). The data analysis plan is outlined in the Data Analysis 
section of the Research Strategy.  
4) Quality Assurance. 
Quarterly data audits will be conducted. Confidentiality protections are outlined above. 
5) Regulatory Issues. 
Potential conflicts of interest will be reported using the upcoming NIH rules for disclosure. Adverse Events 
(AEs)/Serious Adverse Events (SAEs) occurring during the course of the project will be collected, documented, 
and reported in accordance with protocol and Institutional Review Board (IRB) reporting requirements. All 
research staff involved with adverse event reporting will receive general and protocol specific AE/SAE training 
including identification, assessment and evaluation, and documentation and reporting. A research assistant will 
identify any potential adverse events during the course of the study from participant self-report and administration 
of the visit assessments and procedures. The research assistant will provide information to a study physician, 
who will be responsible for AE/SAE assessment and evaluation including a determination of seriousness and 
study relatedness. Any significant actions taken by the local IRB and protocol changes will be relayed to NIDA.   
6) Definition of AE and SAE. 
An Adverse Event (AE) is defined as any untoward medical occurrence in a study subject administered a 
pharmaceutical product that does not necessarily have a causal relationship with this treatment (ICH GCP). Any 
unwanted change, physically, psychologically or behaviorally, that occurs in a study participant during the course 
of the trial is an adverse event. A Serious Adverse Event (SAE) is defined as an adverse event that has one of 
the following outcomes: 
• 
Results in death, 
• 
Is life-threatening, 
• 
Requires inpatient hospitalization or prolongation of existing hospitalization, 
• 
Results in persistent or significant disability/incapacity, 
• 
Is a congenital anomaly/birth defect OR 
• 
Requires intervention to prevent one of the above outcomes. 


7) Documentation and Reporting. 
AEs/SAEs are documented and reported as per protocol and IRB requirements. Research staff will identify 
adverse events and obtain all available information to assess severity, seriousness, study relatedness, 
expectedness, outcome and the need for change or discontinuation in the study intervention. Adverse events 
are generally documented on AE Logs and AE Case Report Forms (CRFs). Additional relevant AE information 
if available should be documented in a progress note in the research record as appropriate to allow monitoring 
and evaluating of the AE. If the AE meets the definition for serious, appropriate SAE protocol specific reporting 
forms are completed and disseminated to the appropriate persons and within the designated timeframes as 
indicated above. For each AE/SAE recorded, the research staff will follow the AE/SAE until resolution, 
stabilization or until the participant is no longer in the study as stated in the protocol. When a reportable SAE is 
identified, the research staff will notify the MUSC IRB within 24 hours and complete the AE report form in 
conjunction with the PI. The MUSC IRB meets monthly and is located at 165 Cannon Street, Rm. 501, 
Charleston, SC  29425. Communication with the IRB is through email, memos, official IRB forms, and online 
reporting. A report will also be sent to the NIH program officer assigned to the project. 
If complete information is not available when the initial 24-hour SAE report is disseminated, follow-up information 
will be gathered to enable a complete assessment and outcome of the event. This information may include 
hospital discharge records, autopsy reports, clinic records, etc. The research staff will attach copies of source 
documents to the SAE report for review by the PI and for forwarding to the NIH program officer as appropriate 
within 2 weeks of the initial SAE report. In addition, the PI will provide a signed, dated SAE summary report, 
which will be sent to the NIDA Medical Safety Officer within two weeks of the initial SAE report. 
We will report adverse events to the MUSC IRB online as soon as possible, but no later than 10 working days 
after the investigator first learns of the event. The MUSC IRB AE reporting requirements are as follows: All deaths 
that occur during the study or 30 days post termination from the study are required to be reported as adverse 
events even if they are expected or unrelated. Other adverse events are reportable to the MUSC IRB if the AE 
is unexpected AND related or possibly related AND serious or more prevalent than expected. All three criteria 
must be met for an AE to be reported to the MUSC IRB. The IRB definition of unexpected is that the AE is not 
identified in nature, severity or frequency in the current protocol, informed consent, investigator brochure or with 
other current risk information. The definition of related is that there is a reasonable possibility that the adverse 
event may have been caused by the drug, device or intervention. Reportable AEs are reviewed by the IRB Chair 
and reported to the IRB Board at the next meeting. 
8) Trial Safety. 
The potential risks and benefits and methods to minimize these risks are outlined above. The research staff will 
report any unexpected AEs or any scores of “severe” on the side-effect symptom rating form or any FDA-defined 
serious AEs to the PI within 24 hrs so that the PI can decide on the appropriate action. All unexpected AEs will 
be monitored while they are active to determine if treatment is needed. Study procedures will follow the FDA’s 
Good Clinical Practice Guidelines (www.fda.gov/oc/gcp). Any outside requests for information or any breaches 
in confidentiality will be reported to Dr. Prisciandaro.  
9) Trial Efficacy. 
An interim analysis is not planned at this time. 
10) DSM Plan Administration. 
Drs. Prisciandaro, Tolliver, McRae-Clark, Anton, and Squeglia will be responsible for monitoring the study, and 
will participate in weekly study meetings. A DSM report will be filed with the IRB and NIDA on a yearly basis, 
unless greater than expected problems occur. The report will include participant characteristics, retention and 
disposition of study participants, quality assurance issues and reports of AEs, significant/unexpected AEs and 
serious AEs. We will report outcomes at the end of the trial. 
11) DSM Board.   
A Data Safety and Monitoring Board will be formed to monitor both the rate and severity of adverse events. This 
panel will include 3 clinicians with expertise in cannabis use and mood disorders and a statistician.   
12) Risk Benefit Ratio. 
The assessments and questionnaires are non-invasive and have inherently minimal risks. Potential risks of 
concern are loss of confidentiality and adverse events to gabapentin or MRI. As discussed above, our research 


team will attempt to minimize these risks. Knowledge gained by the proposed study would help fill an important 
void in development of a potential treatment for co-occurring cannabis use disorder and bipolar disorder. 
 
 
 
 
References 
1. 
Lev-Ran, S., et al., Bipolar disorder and co-occurring cannabis use disorders: characteristics, co-
morbidities and clinical correlates. Psychiatry Res, 2013. 209(3): p. 459-65. 
2. 
Agrawal, A., J.I. Nurnberger, Jr., and M.T. Lynskey, Cannabis involvement in individuals with bipolar 
disorder. Psychiatry Res, 2011. 185(3): p. 459-61. 
3. 
Weinstock, L.M., et al., Demographic and clinical characteristics associated with comorbid cannabis use 
disorders (CUDs) in hospitalized patients with bipolar I disorder. Compr Psychiatry, 2016. 65: p. 57-62. 
4. 
Kvitland, L.R., et al., Continued cannabis use at one year follow up is associated with elevated mood and 
lower global functioning in bipolar I disorder. BMC Psychiatry, 2015. 15: p. 11. 
5. 
van Rossum, I., et al., Does cannabis use affect treatment outcome in bipolar disorder? A longitudinal 
analysis. J Nerv Ment Dis, 2009. 197(1): p. 35-40. 
6. 
Prisciandaro, J.J. and D.H. Myrick, Co-morbid Bipolar and Alcohol Use Disorders: A Treatment-Focused 
Review. Journal of Dual Diagnosis, 2010. 6(2): p. 171-188. 
7. 
Hassel, B. and R. Dingledine, Glutamate, in Basic Neurochemistry: Molecular, Cellular, and Medical 
Aspects, G.J. Siegel, et al., Editors. 2006, Elsevier Academic Press: London, UK. p. 267-290. 
8. 
Olsen, R.W. and H. Betz, GABA and Glycine, in Basic Neurochemistry: Molecular, Cellular, and Medical 
Aspects, G.J. Siegel, et al., Editors. 2006, Elsevier Academic Press: London, UK. p. 291-301. 
9. 
Koob, G.F. and N.D. Volkow, Neurocircuitry of addiction. Neuropsychopharmacology, 2010. 35(1): p. 
217-38. 
10. 
Kalivas, P.W. and C. O'Brien, Drug addiction as a pathology of staged neuroplasticity. 
Neuropsychopharmacology, 2008. 33(1): p. 166-80. 
11. 
Lopez-Moreno, J.A., et al., The pharmacology of the endocannabinoid system: functional and structural 
interactions with other neurotransmitter systems and their repercussions in behavioral addiction. Addict 
Biol, 2008. 13(2): p. 160-87. 
12. 
Ferraro, L., et al., The cannabinoid receptor agonist WIN 55,212-2 regulates glutamate transmission in 
rat cerebral cortex: an in vivo and in vitro study. Cereb Cortex, 2001. 11(8): p. 728-33. 
13. 
Herkenham, M., et al., Characterization and localization of cannabinoid receptors in rat brain: a 
quantitative in vitro autoradiographic study. J Neurosci, 1991. 11(2): p. 563-83. 
14. 
Le-Niculescu, H., et al., Convergent functional genomics of genome-wide association data for bipolar 
disorder: comprehensive identification of candidate genes, pathways and mechanisms. Am J Med Genet 
B Neuropsychiatr Genet, 2009. 150b(2): p. 155-81. 
15. 
Perlis, R.H., et al., Retrospective age at onset of bipolar disorder and outcome during two-year follow-
up: results from the STEP-BD study. Bipolar Disord, 2009. 11(4): p. 391-400. 
16. 
Gerner, R.H., et al., CSF neurochemistry in depressed, manic, and schizophrenic patients compared with 
that of normal controls. Am J Psychiatry, 1984. 141(12): p. 1533-40. 
17. 
Petty, F., et al., Plasma GABA in mood disorders. Psychopharmacol Bull, 1990. 26(2): p. 157-61. 
18. 
Horiuchi, Y., et al., Possible association between a haplotype of the GABA-A receptor alpha 1 subunit 
gene (GABRA1) and mood disorders. Biol Psychiatry, 2004. 55(1): p. 40-5. 
19. 
Massat, I., et al., Excess of allele1 for alpha3 subunit GABA receptor gene (GABRA3) in bipolar patients: 
a multicentric association study. Mol Psychiatry, 2002. 7(2): p. 201-7. 
20. 
Otani, K., et al., The GABA type A receptor alpha5 subunit gene is associated with bipolar I disorder. 
Neurosci Lett, 2005. 381(1-2): p. 108-13. 


21. 
Prescot, A.P., et al., Neurochemical alterations in adolescent chronic marijuana smokers: a proton MRS 
study. Neuroimage, 2011. 57(1): p. 69-75. 
22. 
Prescot, A.P., P.F. Renshaw, and D.A. Yurgelun-Todd, gamma-Amino butyric acid and glutamate 
abnormalities in adolescent chronic marijuana smokers. Drug Alcohol Depend, 2013. 129(3): p. 232-9. 
23. 
Chang, L., et al., Combined and independent effects of chronic marijuana use and HIV on brain 
metabolites. J Neuroimmune Pharmacol, 2006. 1(1): p. 65-76. 
24. 
Muetzel, R.L., et al., In vivo H magnetic resonance spectroscopy in young-adult daily marijuana users. 
Neuroimage Clin, 2013. 2: p. 581-589. 
25. 
Dager, S.R., et al., Brain metabolic alterations in medication-free patients with bipolar disorder. Arch Gen 
Psychiatry, 2004. 61(5): p. 450-8. 
26. 
Ehrlich, A., et al., Alterations of cerebral glutamate in the euthymic state of patients with bipolar disorder. 
Psychiatry Res, 2015. 233(2): p. 73-80. 
27. 
Frye, M.A., et al., Increased anterior cingulate/medial prefrontal cortical glutamate and creatine in bipolar 
depression. Neuropsychopharmacology, 2007. 32(12): p. 2490-9. 
28. 
Michael, N., et al., Acute mania is accompanied by elevated glutamate/glutamine levels within the left 
dorsolateral prefrontal cortex. Psychopharmacology (Berl), 2003. 168(3): p. 344-6. 
29. 
Michael, N., A. Erfurth, and B. Pfleiderer, Elevated metabolites within dorsolateral prefrontal cortex in 
rapid cycling bipolar disorder. Psychiatry Res, 2009. 172(1): p. 78-81. 
30. 
Ongur, D., et al., Abnormal glutamatergic neurotransmission and neuronal-glial interactions in acute 
mania. Biol Psychiatry, 2008. 64(8): p. 718-26. 
31. 
Soeiro-de-Souza, M.G., et al., Bcl-2 rs956572 polymorphism is associated with increased anterior 
cingulate cortical glutamate in euthymic bipolar I disorder. Neuropsychopharmacology, 2013. 38(3): p. 
468-75. 
32. 
Bhagwagar, Z., et al., Reduction in occipital cortex gamma-aminobutyric acid concentrations in 
medication-free recovered unipolar depressed and bipolar subjects. Biol Psychiatry, 2007. 61(6): p. 806-
12. 
33. 
Brady, R.O., Jr., et al., Brain gamma-aminobutyric acid (GABA) abnormalities in bipolar disorder. Bipolar 
Disord, 2013. 15(4): p. 434-9. 
34. 
Wang, P.W., et al., Magnetic resonance spectroscopic measurement of cerebral gamma-aminobutyric 
acid concentrations in patients with bipolar disorders. Acta Neuropsychiatrica, 2006. 18(2): p. 120-126. 
35. 
Swann, A.C., et al., Impulsivity: a link between bipolar disorder and substance abuse. Bipolar Disord, 
2004. 6(3): p. 204-12. 
36. 
Gonzalez, R., et al., Performance of young adult cannabis users on neurocognitive measures of impulsive 
behavior and their relationship to symptoms of cannabis use disorders. J Clin Exp Neuropsychol, 2012. 
34(9): p. 962-76. 
37. 
Swann, A.C., et al., Impulsivity and phase of illness in bipolar disorder. J Affect Disord, 2003. 73(1-2): p. 
105-11. 
38. 
Murphy, E.R., et al., Impulsive behaviour induced by both NMDA receptor antagonism and GABAA 
receptor activation in rat ventromedial prefrontal cortex. Psychopharmacology (Berl), 2012. 219(2): p. 
401-10. 
39. 
Pattij, T. and L.J. Vanderschuren, The neuropharmacology of impulsive behaviour. Trends Pharmacol 
Sci, 2008. 29(4): p. 192-9. 
40. 
Ende, G., et al., Impulsivity and Aggression in Female BPD and ADHD Patients: Association with ACC 
Glutamate and GABA Concentrations. Neuropsychopharmacology, 2016. 41(2): p. 410-8. 
41. 
Silveri, M.M., et al., Frontal lobe gamma-aminobutyric acid levels during adolescence: associations with 
impulsivity and response inhibition. Biol Psychiatry, 2013. 74(4): p. 296-304. 
42. 
Altshuler, L.L., et al., Blunted activation in orbitofrontal cortex during mania: a functional magnetic 
resonance imaging study. Biol Psychiatry, 2005. 58(10): p. 763-9. 


43. 
Tapert, S.F., et al., Functional MRI of inhibitory processing in abstinent adolescent marijuana users. 
Psychopharmacology (Berl), 2007. 194(2): p. 173-83. 
44. 
van Veenendaal, T.M., et al., Metabolic and functional MR biomarkers of antiepileptic drug effectiveness: 
A review. Neurosci Biobehav Rev, 2015. 59: p. 92-9. 
45. 
Cai, K., et al., The impact of gabapentin administration on brain GABA and glutamate concentrations: a 
7T (1)H-MRS study. Neuropsychopharmacology, 2012. 37(13): p. 2764-71. 
46. 
Kuzniecky, R., et al., Modulation of cerebral GABA by topiramate, lamotrigine, and gabapentin in healthy 
adults. Neurology, 2002. 58(3): p. 368-72. 
47. 
Petroff, O.A., et al., Effects of gabapentin on brain GABA, homocarnosine, and pyrrolidinone in epilepsy 
patients. Epilepsia, 2000. 41(6): p. 675-80. 
48. 
Petroff, O.A., et al., The effect of gabapentin on brain gamma-aminobutyric acid in patients with epilepsy. 
Ann Neurol, 1996. 39(1): p. 95-9. 
49. 
Goldberg, J.F. and K.E. Burdick, Cognitive side effects of anticonvulsants. J Clin Psychiatry, 2001. 62 
Suppl 14: p. 27-33. 
50. 
Aracil-Fernandez, A., P. Almela, and J. Manzanares, Pregabalin and topiramate regulate behavioural 
and brain gene transcription changes induced by spontaneous cannabinoid withdrawal in mice. Addict 
Biol, 2013. 18(2): p. 252-62. 
51. 
Lile, J.A., T.H. Kelly, and L.R. Hays, Separate and combined effects of the GABA(B) agonist baclofen 
and Δ(9)-THC in humans discriminating Δ(9)-THC. Drug and alcohol dependence, 2012. 126(1-2): p. 
216-223. 
52. 
Lile, J.A., et al., Separate and combined effects of gabapentin and [INCREMENT]9-tetrahydrocannabinol 
in humans discriminating [INCREMENT]9-tetrahydrocannabinol. Behav Pharmacol, 2016. 27(2-3 Spec 
Issue): p. 215-24. 
53. 
de Guglielmo, G., et al., Pregabalin reduces cocaine self-administration and relapse to cocaine seeking 
in the rat. Addiction Biology, 2013. 18(4): p. 644-653. 
54. 
Roberto, M., et al., Cellular and behavioral interactions of gabapentin with alcohol dependence. J 
Neurosci, 2008. 28(22): p. 5762-71. 
55. 
Filip, M., et al., Various GABA-mimetic drugs differently affect cocaine-evoked hyperlocomotion and 
sensitization. Eur J Pharmacol, 2006. 541(3): p. 163-70. 
56. 
Kurokawa, K., et al., Gabapentin blocks methamphetamine-induced sensitization and conditioned place 
preference via inhibition of alpha(2)/delta-1 subunits of the voltage-gated calcium channels. 
Neuroscience, 2011. 176: p. 328-35. 
57. 
Mason, B.J., et al., A proof-of-concept randomized controlled study of gabapentin: effects on cannabis 
use, 
withdrawal 
and 
executive 
function 
deficits 
in 
cannabis-dependent 
adults. 
Neuropsychopharmacology, 2012. 37(7): p. 1689-98. 
58. 
Sherman, B.J. and A.L. McRae-Clark, Treatment of Cannabis Use Disorder: Current Science and Future 
Outlook. Pharmacotherapy, 2016. 36(5): p. 511-35. 
59. 
Berlin, R.K., P.M. Butler, and M.D. Perloff, Gabapentin Therapy in Psychiatric Disorders: A Systematic 
Review. The Primary Care Companion for CNS Disorders, 2015. 17(5): p. 10.4088/PCC.15r01821. 
60. 
Pande, A.C., et al., Gabapentin in bipolar disorder: a placebo-controlled trial of adjunctive therapy. 
Gabapentin Bipolar Disorder Study Group. Bipolar Disord, 2000. 2(3 Pt 2): p. 249-55. 
61. 
Frye, M.A., et al., A placebo-controlled study of lamotrigine and gabapentin monotherapy in refractory 
mood disorders. J Clin Psychopharmacol, 2000. 20(6): p. 607-14. 
62. 
Vieta, E., et al., A double-blind, randomized, placebo-controlled, prophylaxis study of adjunctive 
gabapentin for bipolar disorder. J Clin Psychiatry, 2006. 67(3): p. 473-7. 
63. 
Rakofsky, J.J. and B.W. Dunlop, Treating nonspecific anxiety and anxiety disorders in patients with 
bipolar disorder: a review. J Clin Psychiatry, 2011. 72(1): p. 81-90. 
64. 
Tolliver, B.K., et al., A randomized, double-blind, placebo-controlled clinical trial of acamprosate in 
alcohol-dependent individuals with bipolar disorder: a preliminary report. Bipolar Disord, 2012. 14(1): p. 
54-63. 


65. 
McRae-Clark, A.L., et al., Buspirone treatment of cannabis dependence: A randomized, placebo-
controlled trial. Drug Alcohol Depend, 2015. 156: p. 29-37. 
66. 
Prisciandaro, J.J., et al., Associations between recent heavy drinking and dorsal anterior cingulate N-
acetylaspartate and glutamate concentrations in non-treatment seeking individuals with alcohol 
dependence. Alcohol Clin Exp Res, 2016 in press. 
67. 
Association, A.P., Diagnostic and Statistical Manual of Mental Disorders. 5th ed. 2013, Washington, DC. 
68. 
Martz, M.E., et al., Association of marijuana use with blunted nucleus accumbens response to reward 
anticipation. JAMA Psychiatry, 2016. 73(8): p. 838-844. 
69. 
Cousijn, J., et al., Neural responses associated with cue-reactivity in frequent cannabis users. Addict 
Biol, 2013. 18(3): p. 570-80. 
70. 
Filbey, F.M., et al., Marijuana craving in the brain. Proc Natl Acad Sci U S A, 2009. 106(31): p. 13016-
21. 
71. 
Bermpohl, F., et al., Altered representation of expected value in the orbitofrontal cortex in mania. Hum 
Brain Mapp, 2010. 31(7): p. 958-69. 
72. 
Hassel, S., et al., Elevated striatal and decreased dorsolateral prefrontal cortical activity in response to 
emotional stimuli in euthymic bipolar disorder: no associations with psychotropic medication load. Bipolar 
Disord, 2008. 10(8): p. 916-27. 
73. 
Lawrence, N.S., et al., Subcortical and ventral prefrontal cortical neural responses to facial expressions 
distinguish patients with bipolar disorder and major depression. Biol Psychiatry, 2004. 55(6): p. 578-87. 
74. 
Prisciandaro, J.J., et al., The relationship between years of cocaine use and brain activation to cocaine 
and response inhibition cues. Addiction, 2014. 109(12): p. 2062-2070. 
75. 
Prisciandaro, J.J., et al., Prospective associations between brain activation to cocaine and no-go cues 
and cocaine relapse. Drug and Alcohol Dependence, 2013. 131(1–2): p. 44-49. 
76. 
Phillips, M.L., et al., Medication effects in neuroimaging studies of bipolar disorder. Am J Psychiatry, 
2008. 165(3): p. 313-20. 
77. 
Lindquist, D.M., R.S. Dunn, and K.M. Cecil, Long term antipsychotic treatment does not alter metabolite 
concentrations in rat striatum: an in vivo magnetic resonance spectroscopy study. Schizophr Res, 2011. 
128(1-3): p. 83-90. 
78. 
Merritt, K., et al., Nature of Glutamate Alterations in Schizophrenia: A Meta-analysis of Proton Magnetic 
Resonance Spectroscopy Studies. JAMA Psychiatry, 2016. 73(7): p. 665-74. 
79. 
Soeiro-de-Souza, M.G., et al., Anterior cingulate Glutamate-Glutamine cycle metabolites are altered in 
euthymic bipolar I disorder. Eur Neuropsychopharmacol, 2015. 25(12): p. 2221-9. 
80. 
Swann, A.C., et al., Severity of bipolar disorder is associated with impairment of response inhibition. J 
Affect Disord, 2009. 116(1-2): p. 30-6. 
81. 
First, M.B., et al., Structured Clinical Interview for DSM-5. 2015, Arlington, VA: American Psychiatric 
Association. 
82. 
Patton, J.H., M.S. Stanford, and E.S. Barratt, Factor structure of the Barratt impulsiveness scale. J Clin 
Psychol, 1995. 51(6): p. 768-74. 
83. 
Sobell, L.C. and M.B. Sobell, Alcohol Timeline Followback Users' Manual. 1995, Toronto, Canada: 
Addiction Research Foundation. 
84. 
Mariani, J.J., et al., Quantification and comparison of marijuana smoking practices: blunts, joints, and 
pipes. Drug Alcohol Depend, 2011. 113(2-3): p. 249-51. 
85. 
Heishman, S.J., et al., Reliability and validity of a short form of the Marijuana Craving Questionnaire. 
Drug Alcohol Depend, 2009. 102(1-3): p. 35-40. 
86. 
Allsop, D.J., et al., The Cannabis Withdrawal Scale development: patterns and predictors of cannabis 
withdrawal and distress. Drug Alcohol Depend, 2011. 119(1-2): p. 123-9. 
87. 
Young, R.C., et al., A rating scale for mania: reliability, validity and sensitivity. Br J Psychiatry, 1978. 133: 
p. 429-35. 


88. 
Montgomery, S.A. and M. Asberg, A new depression scale designed to be sensitive to change. Br J 
Psychiatry, 1979. 134: p. 382-9. 
89. 
Beck, A.T., et al., Comparison of Beck Depression Inventories -IA and -II in psychiatric outpatients. J 
Pers Assess, 1996. 67(3): p. 588-97. 
90. 
Beck, A. and R.A. Steer, Beck Anxiety Inventory Manual. 1983, San Antonio, TX: Psychological 
Corporation. 
91. 
Buysse, D.J., et al., The Pittsburgh sleep quality index: A new instrument for psychiatric practice and 
research. Psychiatry Research. 28(2): p. 193-213. 
92. 
Posner, K., et al., The Columbia–Suicide Severity Rating Scale: Initial Validity and Internal Consistency 
Findings From Three Multisite Studies With Adolescents and Adults. The American journal of psychiatry, 
2011. 168(12): p. 1266-1277. 
93. 
Schwilke, E.W., et al., Differentiating new cannabis use from residual urinary cannabinoid excretion in 
chronic, daily cannabis users. Addiction, 2011. 106(3): p. 499-506. 
94. 
Rose, M.A. and P.C. Kam, Gabapentin: pharmacology and its use in pain management. Anaesthesia, 
2002. 57(5): p. 451-62. 
95. 
Katzung, B.G., S.B. Masters, and A.J. Trevor, Basic & Clinical Pharmacology. 12th ed. 2012, USA: 
McGraw-Hill Medical. 
96. 
Anton, R.F., et al., Efficacy of a combination of flumazenil and gabapentin in the treatment of alcohol 
dependence: relationship to alcohol withdrawal symptoms. J Clin Psychopharmacol, 2009. 29(4): p. 334-
42. 
97. 
Anton, R.F., et al., Gabapentin combined with naltrexone for the treatment of alcohol dependence. Am J 
Psychiatry, 2011. 168(7): p. 709-17. 
98. 
Myrick, H., et al., A double-blind trial of gabapentin versus lorazepam in the treatment of alcohol 
withdrawal. Alcohol Clin Exp Res, 2009. 33(9): p. 1582-8. 
99. 
Juenke, J.M., et al., Performance characteristics of the ARK diagnostics gabapentin immunoassay. Ther 
Drug Monit, 2011. 33(4): p. 398-401. 
100. 
Gilron , I., et al., Morphine, Gabapentin, or Their Combination for Neuropathic Pain. New England Journal 
of Medicine, 2005. 352(13): p. 1324-1334. 
101. 
Pandey, C.K., et al., Gabapentin for the treatment of pain in guillain-barre syndrome: a double-blinded, 
placebo-controlled, crossover study. Anesth Analg, 2002. 95(6): p. 1719-23, table of contents. 
102. 
Durst, C.R., et al., Noninvasive evaluation of the regional variations of GABA using magnetic resonance 
spectroscopy at 3 Tesla. Magn Reson Imaging, 2015. 33(5): p. 611-7. 
103. 
Haber, S.N. and B. Knutson, The reward circuit: linking primate anatomy and human imaging. 
Neuropsychopharmacology, 2010. 35(1): p. 4-26. 
104. 
Hermann, D., et al., Translational magnetic resonance spectroscopy reveals excessive central glutamate 
levels during alcohol withdrawal in humans and rats. Biol Psychiatry, 2012. 71(11): p. 1015-21. 
105. 
Liu, B., et al., Alterations of GABA and glutamate-glutamine levels in premenstrual dysphoric disorder: a 
3T proton magnetic resonance spectroscopy study. Psychiatry Res, 2015. 231(1): p. 64-70. 
106. 
Aufhaus, E., et al., Absence of changes in GABA concentrations with age and gender in the human 
anterior cingulate cortex: a MEGA-PRESS study with symmetric editing pulse frequencies for 
macromolecule suppression. Magn Reson Med, 2013. 69(2): p. 317-20. 
107. 
Mullins, P.G., et al., Comparative reliability of proton spectroscopy techniques designed to improve 
detection of J-coupled metabolites. Magn Reson Med, 2008. 60(4): p. 964-9. 
108. 
Edden, R.A., et al., Gannet: A batch-processing tool for the quantitative analysis of gamma-aminobutyric 
acid-edited MR spectroscopy spectra. J Magn Reson Imaging, 2014. 40(6): p. 1445-52. 
109. 
Provencher, S.W., Estimation of metabolite concentrations from localized in vivo proton NMR spectra. 
Magn Reson Med, 1993. 30(6): p. 672-9. 


110. 
Harris, A.D., N.A. Puts, and R.A. Edden, Tissue correction for GABA-edited MRS: Considerations of 
voxel composition, tissue segmentation, and tissue relaxations. J Magn Reson Imaging, 2015. 42(5): p. 
1431-40. 
111. 
MacKinnon, D.P., A.J. Fairchild, and M.S. Fritz, Mediation Analysis. Annual review of psychology, 2007. 
58: p. 593. 
112. 
Little, R.J.A. and D.B. Rubin, Statistical Analysis with Missing Data. 2nd ed. 2002, USA: Wiley-
Interscience. 
113. 
Chang, L., C.S. Jiang, and T. Ernst, Effects of age and sex on brain glutamate and other metabolites. 
Magn Reson Imaging, 2009. 27(1): p. 142-5. 
114. 
Mason, G.F., et al., Cortical gamma-aminobutyric acid levels and the recovery from ethanol dependence: 
preliminary evidence of modification by cigarette smoking. Biol Psychiatry, 2006. 59(1): p. 85-93. 
115. 
O'Gorman, R.L., et al., In vivo detection of GABA and glutamate with MEGA-PRESS: reproducibility and 
gender effects. J Magn Reson Imaging, 2011. 33(5): p. 1262-7. 
116. 
Simon, N.M., et al., Anxiety disorder comorbidity in bipolar disorder patients: data from the first 500 
participants in the Systematic Treatment Enhancement Program for Bipolar Disorder (STEP-BD). Am J 
Psychiatry, 2004. 161(12): p. 2222-9. 
117. 
Grant, B.F., et al., Prevalence and co-occurrence of substance use disorders and independent mood and 
anxiety disorders: results from the National Epidemiologic Survey on Alcohol and Related Conditions. 
Arch Gen Psychiatry, 2004. 61(8): p. 807-16. 
118. 
Puts, N.A. and R.A. Edden, In vivo magnetic resonance spectroscopy of GABA: a methodological review. 
Prog Nucl Magn Reson Spectrosc, 2012. 60: p. 29-41. 
119. 
Mon, A., T.C. Durazzo, and D.J. Meyerhoff, Glutamate, GABA, and other cortical metabolite 
concentrations during early abstinence from alcohol and their associations with neurocognitive changes. 
Drug Alcohol Depend, 2012. 125(1-2): p. 27-36.