Subechhya Pradhan1, Anouk Marsman1, Rebecca Ward2, Candice Ford2, Ashley Lloyd2, David Schretlen1,2, Akira Sawa2, and Peter B. Barker1,3
1The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States, 2Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, United States, 3Radiology, Kennedy Krieger Institute, Baltimore, MD, United States
Synopsis
Imbalance
in glutamatergic systems is implicated in the pathophysiology of psychosis. The
purpose of this study was to assess differences in metabolite levels between
subjects with a first episode of psychosis (FEP) and healthy controls, and to
study correlations between metabolites and measures of disease severity,
including neuropsychological scales, positive and negative symptoms.Introduction
Glutamatergic and GABAergic systems are believed to play a
role in the pathophysiology of psychosis
1,2. This abstract presents
results from an interim analysis of an ongoing study the differences in
metabolite levels along with metabolite correlations with neuropsychiatric
measures in first episode psychosis (FEP) subjects and healthy controls from
our on going study.
Methods
45 FEP subjects and 70 healthy controls participated in this
study to date. All FEP subjects had a diagnosis of psychosis (43.8%
schizophrenia) and were recruited within the first two years of disease onset
and were on antipsychotic medication at the time of the scan. All participants
underwent a set of neuropsychiatric evaluations
3 (CNNS), and the FEP
subjects also underwent positive and negative symptom rating (SAPS and SANS).
MR
methods: Participants were scanned using a 7T scanner (Philips
‘Achieva’, Best, Netherlands) equipped with a 32-channel head coil (Nova
Medical, Orlando, FL). Spectra were recorded from anterior cingulate cortex (ACC; 30x20x20 mm
3,
Figure 1), left centrum semiovale (CSO; 40x20x15 mm
3), left
dorsolateral prefrontal cortex (DLPFC; 25x20x20 mm
3), left
orbitofrontal cortex (OFC; 20x20x20 mm
3), and bilateral thalamus (Thal,
20x30x15 mm
3) using a STEAM
sequence (TE/TM/TR=14/33/3000 ms, 128 NEX, 16 NEX water). Spectra were analyzed in LCModel
4 using
water as an internal reference and a basis set simulated in VESPA
5.
Statistical
analysis: Differences between groups were compared using students
t-test, and linear regression performed for GABA, Glu, Gln, GSH, NAA, NAAG,
tCr, tCho and tNAA concentrations vs. composite CNNS scores, SAPS and SANS.
Results
Representative spectrum from the ACC along with LCModel fit is shown in Figure 1. Metabolite levels
that were significantly different between FEP and control subjects are given in
Table 1. In patients, significant positive
correlations were found between CNNS scores and GABA (p =0.024) , NAAG (p=0.008)
and tCho (p=0.017) in the OFC, significant negative correlation between SAPS score
and OFC NAA (p=0.039); and significant negative correlation between SANS rating
scale and ACC GABA (p=0.042), CSO Glu (p=0.007), CSO Glx (p=0.013) and OFC GABA
(p=0.018).
Discussion
Reductions in NAA in FEP in cortical regions and thalamus
are consistent with neuronal damage/dysfunction in these regions. In addition,
Gln was increased in DLPFC and CSO, Glu decreased in ACC, and NAAG decreased in
CSO, suggesting possible glutamatergic dysfunction in multiple brain regions.
Glutamatergic metabolite levels also correlated with measures of disease
severity (e.g. the negative correlation of SANS with ACC GABA, CSO Glu, CSO Glx and OFC
GABA) further suggesting a central role of these metabolites in the
pathophysiology of psychosis. However, a larger sample size and further analyses
are required to confirm these interim findings.
Acknowledgements
NIH grants R01MH096263, R01MH092443; Mitsubishi
Tanabe Pharma CorporationReferences
1.Rowland et al. Schizophrenia Bulletin 2013: 39:1096-104;
2. Theberge et al. Am J Psychiatry 2002: 159: 1944-46; 3. Testa et al. J
Int Neuropsychol Soc. 2009: 15:1012-22. 4. Provencher, S.W; MRM. 1993;
30:672-679; 5. http://scion.duhs.duke.edu/vespa/simulation