Hu Cheng1, Derek Kellar1, Ulrike Dydak2,3, Peter Finn1, Allison Lake 1, Shalmali Dharmadhikari2,3, George Rebec 1, and Sharlene Newman1
1Psychological and Brain Sciences, Indiana University, Bloomington, IN, United States, 2School of Health Sciences, Purdue University, West Lafayette, IN, United States, 3Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, United States
Synopsis
Evidence indicates that glutamate
neurotransmission plays a critical role in alcohol and other substance
addiction. This study investigated the dynamic change of glutamate level elicited by alcohol cues in individuals with alcohol use disorder (AUD). Both the absolute value of glutamate
concentration and its ratio to total creatine measured decreased
significantly for AUD subjects after they
viewed the pictures of alcoholic beverages. A high correlation (r = -0.90) between baseline
glutamate level and alcohol problem counts was observed for AUD subjects. This cue induced decrease of
glutamate is not a direct translation from animal studies. Introduction
Alcohol use disorder (AUD) impacts a significant number of Americans and
has an impact on both the economy and healthcare. Evidence indicates that
glutamate neurotransmission plays a critical role in alcohol and other
substance addiction. It is believed that the glutamate system is disturbed by
acute and chronic alcohol exposure and as a result leads to cue induced and
alcohol induced reinstatement of drinking during withdrawal. The majority of
the research investigating the relationship between brain glutamate and
addiction has been conducted with animal models. Although few studies reported
higher glutamate levels in alcohol-dependent patients compared with normal
controls
1, how the glutamate system interacts with craving effects over
the course of alcohol dependence remains unknown in humans. The aim of this
study is to explore dynamic changes of glutamate associated with the craving
effect for early developed alcohol use disorder. 1H-MR spectroscopy (MRS) was
employed to quantify glutamate level changes in response to alcohol cues in
individuals with AUD and social drinkers.
Methods
13 individuals with AUD (4 females,
23.1±2.5y) and 15 controls (social drinkers; 6 females, 22.5±3.0y) participated
in the study. AUD subjects met criteria for moderate or severe AUD based on
DSM-V criteria using the Semi-Structured Assessment for the Genetics of Alcoholism
(SSAGA)
2; control subjects had no history of any AUD. Lifetime
alcohol and marijuana problem counts were calculated as the sum of positive
responses pertaining to alcohol or marijuana use, respectively, as reported on
the SSAGA.
All subjects were
scanned on a 3 Tesla Siemens TIM Trio scanner. All subjects were instructed not
to drink alcohol 12 hours prior to the scan which was ensured by a breath
alcohol test. A T1-weighted high-resolution anatomical image was acquired with the
MP-RAGE sequence, followed by two single-voxel MRS scans 15 minutes apart. The
PRESS sequence was used for MRS on a voxel (15 mm x 30 mm x 20 mm) in the
anterior cingulate cortex (ACC): TR/TE = 2000/30 ms, bandwidth = 2000 Hz, 2048
data points, number of measurements = 120, scan time = 4 min, followed by a
water reference scan (8 averages). During the first MRS scan, a total of 60 furniture
pictures (Fig. 1A) were shown to the subjects in a random order These pictures
were changed to pictures of alcoholic beverages from University of Arkansas
3
(Fig. 1B) six minutes before the second MRS scan until the scan ended. After
each MRS scan session, the subjects were asked to rate their craving on a scale
of 1 to 5 with 1 meaning little to no craving and 5 meaning extreme craving.
The spectra data
were processed with LCModel to quantify glutamate concentrations along with
other metabolites including total NAA (tNAA), Choline (Cho), and total creatine
(tCr). The baseline metabolite levels were compared between AUD and controls,
and between furniture cues and alcohol cues, using two-sample t-tests. We also examined
the correlation between baseline glutamate level and total alcohol problem
counts after excluding AUD subjects with other drug problems (9 AUD subjects
left).
Results
AUD subjects reported more craving scores than controls (p = 0.021), indicating the alcoholic beverage pictures did induce a craving effect. Both the absolute value of glutamate concentration and its ratio to total creatine (Glu/tCr) measured decreased significantly for AUD subjects during the second MRS scan, i.e. while they viewed the pictures of alcoholic beverages. This was not the case for controls. No significant change of other metabolites was found, as shown in Fig. 2. Fig. 3 displays the glutamate level as well as Glu/tCr for different cohorts and conditions. There is no significant difference of baseline glutamate level between AUD and controls. However, a high correlation (r = -0.90) between baseline glutamate level and alcohol problem counts was observed for AUD subjects, as shown in Fig. 4.
Discussions
This is the first in vivo study seeing glutamate decrease in
alcohol depedent individuals induced by alcohol cues. The subjects typically
developed AUD within 2-3 years before the scan. This observation suggests that
the homeostasis of the glutamatergic system can be affected by the craving
effect in early alcohol dependence in humans, which is consistent with the
negative correlation between baseline glutamate level and alcohol problem
counts. To our knowledge, the cue induced decrease of glutamate is not a direct
translation from animal studies. In contrast, animal studies have shown
elevated glutamate level in ACC and nucleus accumbens associated with craving
4.
The discrepancy could be due to the difference in the stage of alcohol
dependence and the underlying neurobiological cause of craving.
Acknowledgements
We thank Dr. Lindsay Ham and David Lovett from University of Arkansas for providing us the pictures of alcoholic beverages .References
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