A, Axial and sagittal T1-weighted images showing the locations of the 5 brain regions (red boxes) used for MRS in a healthy participant. B-D, Sample MRS spectra from a healthy participant with LCModel fitting output (heavy red lines) superimposed on the original data (black lines) are shown for the centrum semiovale (CSO) (B), dorsolateral prefrontal cortex (DLPFC) (C), and anterior cingulate cortex (ACC) (D). The residual signals following fitting are shown at the top of each panel. LCModel estimated baselines are shown by the gray lines. GABA indicates γ-aminobutyric acid; Gln, glutamine; Glu, glutamate, Glx, glutamate plus glutamine; GSH, glutathione; IU, institutional units; L, left; Lac, lactate; Lip, lipid; NAA, N-acetylaspartate; NAAG, N-acetylaspartyl glutamate; ml, myo-inositol; OFR, orbital frontal cortex; R, right; tCho, phosphocholine plus glycerophosphocholine; tCr, creatine plus phosphocreatine; and Thal, thalamus.
Values represent means and SDs. Abbreviations are defined in the legend to Figure 1.
aSignificant differences after correcting for the false-discovery rate.
Values represent means and SDs. No significant differences in voxel composition are found between participants with first-episode psychosis (FEP) and healthy control (HC) participants. ACC indicates anterior cingulate cortex; CSO, centrum semiovale, DLPFC, dorsolateral prefrontal cortex; OFR, orbital frontal cortex; and Thal, thalamus.
eTable 1. Metabolite levels (Mean ± Standard Deviation, i.u.), Cramer-Rao Lower Bounds (Mean CRLB, %), Sample Size (N) and P-Values From ANCOVA Analysis for All 5 Brain Regions
eTable 2. Spectral SNR and Linewidth (FWHM) Values for FEP and HC Groups
eTable 3. Correlations (r Values) Between Metabolite Levels and Neuropsychological Performance
eFigure. Partial Correlation Between the NAA Level in the CSO and Processing Speed Scores While Adjusting for Age, Sex, Education, and Regional CSF Content.
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Wang AM, Pradhan S, Coughlin JM, et al. Assessing Brain Metabolism With 7-T Proton Magnetic Resonance Spectroscopy in Patients With First-Episode Psychosis. JAMA Psychiatry. 2019;76(3):314–323. doi:10.1001/jamapsychiatry.2018.3637
Can localized magnetic resonance spectroscopy performed at 7 T detect metabolic changes early in the course of a first-episode psychosis, and are these associated with neuropsychological performance?
Eighty-one patients with first-episode psychosis were compared to 91 age-matched control participants; decreased levels of N-acetylaspartate were found in several brain regions, as well as selective regional decreases in glutamate, glutathione and γ-aminobutyric acid.
Multiple metabolic abnormalities can be detected by 7-T magnetic resonance spectroscopy in patients with first-episode psychosis, which correlated with performance on neuropsychological tests.
The use of high-field magnetic resonance spectroscopy (MRS) in multiple brain regions of a large population of human participants facilitates in vivo study of localized or diffusely altered brain metabolites in patients with first-episode psychosis (FEP) compared to healthy participants.
To compare metabolite levels in 5 brain regions between patients with FEP (evaluated within 2 years of onset) and healthy controls, and to explore possible associations between targeted metabolite levels and neuropsychological test performance.
Design, Setting, and Participants
Cross-sectional design used 7-T MRS at a research MR imaging facility in participants recruited from clinics at the Johns Hopkins Schizophrenia Center and the local population. Eighty-one patients who had received a DSM-IV diagnosis of FEP within the last 2 years and 91 healthy age-matched (but not sex-matched) volunteers participated.
Main Outcomes and Measures
Brain metabolite levels including glutamate, glutamine, γ-aminobutyric acid (GABA), N-acetylaspartate, N-acetylaspartyl glutamate, and glutathione, as well as performance on neuropsychological tests.
The mean (SD) age of 81 patients with FEP was 22.3 (4.4) years and 57 were male, while the mean (SD) age of 91 healthy participants was 23.3 (3.9) years and 42 were male. Compared with healthy participants, patients with FEP had lower levels of glutamate (F1,162 = 8.63, P = .02), N-acetylaspartate (F1,161 = 5.93, P = .03), GABA (F1,163 = 6.38, P = .03), and glutathione (F1,162 = 4.79, P = .04) in the anterior cingulate (all P values are corrected for multiple comparisons); lower levels of N-acetylaspartate in the orbitofrontal region (F1,136 = 7.23, P = .05) and thalamus (F1,133 = 6.78, P = .03); and lower levels of glutathione in the thalamus (F1,135 = 7.57, P = .03). Among patients with FEP, N-acetylaspartate levels in the centrum semiovale white matter were significantly correlated with performance on neuropsychological tests, including processing speed (r = 0.48; P < .001), visual (r = 0.33; P = .04) and working (r = 0.38; P = .01) memory, and overall cognitive performance (r = 0.38; P = .01).
Conclusions and Relevance
Seven-tesla MRS offers insights into biochemical changes associated with FEP and may be a useful tool for probing brain metabolism that ranges from neurotransmission to stress-associated pathways in participants with psychosis.
Improved understanding of the biochemical processes underlying the development of psychosis is of key importance in the development of new therapeutic strategies. While psychosis and schizophrenia are traditionally thought of as primarily involving the dopaminergic neurotransmitter system, other neurotransmitters have increasingly been implicated, including the glutamatergic and γ-aminobutyric acid (GABA)-ergic systems.1-4 Other lines of evidence have also implicated aberrant homeostatic signaling or stress-associated pathways in its pathophysiology, such as altered redox signaling5 and immune signaling,6,7 across psychosis.
There are relatively few techniques available that can noninvasively probe biochemistry in the human brain. Positron emission tomography is traditionally used to investigate cerebral blood flow, glucose metabolism, cellular processes, and receptor occupancy, while proton magnetic resonance spectroscopy (MRS) offers complementary information on various different brain metabolites, including those related to neuronal and glial cell metabolism, energy metabolites, selected neurotransmitters, antioxidants, and others.8 Whereas each radiotracer for positron emission tomography imaging is designed to specifically bind an individual molecular target in the brain, MRS has the ability to measure multiple compounds at the same time, allowing a “survey” of cerebral metabolism without administering any exogenous agent. MRS has been extensively used to study both first-episode psychosis (FEP)9,10 and schizophrenia in the past, but nearly all of these studies used the commonly available magnetic field strengths of 1.5 or 3 T.11,12
In MRS, sensitivity and spectral resolution increase with increasing magnetic field strength, and it has been unambiguously demonstrated that MRS at 7 T allows the estimation of more compounds at higher precision than at lower field strength.13,14 In particular, the ability to accurately estimate levels of compounds which have small and/or overlapping signals in brain spectra is enhanced at 7 T. Examples include the ability to resolve glutamate (Glu) from glutamine (Gln), N-acetylaspartylglutamate (NAAG) from N-acetylaspartate (NAA), as well as to measure glutathione (GSH) and GABA with greater accuracy than at 3 T.13,14 Seven tesla MRS has also been shown to give highly reproducible results, even for some of the lower intensity metabolites, such as GABA, Gln, and NAAG.15 To date, as far as we are aware, there have only been 7 prior 7-T MRS studies in patients with FEP or schizophrenia,16-22 each of which involve cohorts of between 20 to 30 participants.
The purpose of the present study, therefore, was to apply 7-T MRS to participants with a diagnosis of FEP (within 2 years of diagnosis) and to compare metabolite levels to a similar group of healthy control (HC) participants. The main novel aspects of the study compared to previous 7-T MRS studies were the inclusion of more (5) brain regions in much larger cohorts of FEP and HC participants. The 5 brain regions were chosen because of their key importance in psychosis and schizophrenia.23-29 The anterior cingulate cortex (ACC) and dorsolateral prefrontal cortex (DLPFC) have long been implicated in psychosis from both imaging and pathology perspectives.19,24,26,28-31 Similarly, the thalamus is a “nodal link” for multiple functional neurocircuits, in particular those connecting with the cerebral cortex, and previous morphometric imaging studies have suggested preferentially reduced volumes in the thalamus.23,28,29 The orbitofrontal region (OFR) is chosen as a referential area to the DLPFC within the prefrontal cortex and has also been implicated in psychosis.32 The centrum semiovale (CSO) is included since it is a large white matter free from gray matter, and the white matter is also implicated in the pathology of psychosis.27,33 In addition, previous studies have shown that brain metabolite levels were correlated with cognitive performance in psychosis34-36; hence, we expanded this study by using multiple neuropsychological measures as correlates to further explore the relationships between metabolite level and cognition.
Patients were recruited from patients with FEP within 24 months of first onset of psychotic symptoms as assessed by study team psychiatrists using the Structured Clinical Interview for DSM-IV and collateral information gathered from available medical records. Before the imaging visit, patients were assessed for medical stability during a screening interview (59 ± 50 days prior to imaging) and a clinical interview (28 ± 36 days prior to imaging) and showed no change in outpatient status or robust change in medication regimen between each assessment and the imaging. The diagnosis of psychotic disorder was identified using the Structured Clinical Interview for DSM-IV (Table), and participants were scanned within 24 months of first psychotic symptoms. Exclusion criteria are given in the eAppendix in the Supplement. This study was approved by the Johns Hopkins Medicine Institutional Review Board, and all participants provided written informed consent.
All participants were scanned from January 9, 2014, to March 28, 2017, using a 7-T scanner (Achieva; Philips) equipped with a 32-channel head coil (Nova Medical). All participants were given instructions to lie still and relax. The T1-weighted anatomical images were acquired for spectroscopic voxel placement and tissue segmentation using sagittal 3-dimensional magnetization-prepared rapid acquisition with gradient echo (field of view, 220 × 220 × 180 mm3; isotropic resolution, 0.8 mm; echo time, 1.9 milliseconds; repetition time, 4.4 milliseconds; flip angle, 7°; SENSE factor, 4; scan time, approximately 4 minutes). Magnetic resonance spectra were recorded from 5 brain regions as shown in Figure 1: bilateral dorsal ACC (20 × 30 × 20 mm3, left-right × anterior-posterior × superior-inferior), left CSO (20 × 40 × 15 mm3), left DLPFC (20 × 25 × 20 mm3), left OFR (20 × 20 × 20 mm3), and bilateral thalamus (30 × 20 × 15 mm3) using a STEAM (stimulated echo acquisition mode) sequence (with echo time, 14 milliseconds; repetition time, 3000 milliseconds; mixing time, 33 milliseconds; 16-step phase cycle; and number of excitations, 128). The minimum possible echo time was chosen in order to minimize T2 relaxation and J modulation effects.
Prior to MRS data collection, shimming was adjusted up to second order using a FASTMAP routine, and radio frequency power was optimized on the localized voxel.37 A VAPOR (variable power and optimized relaxation delays) water suppression module was used to acquire water-suppressed metabolite spectra.38 In addition, a scan without water suppression with the same echo and repetition times as the water-suppressed scan was also acquired from each voxel (number of excitations, 2; 2-step phase cycle). Scan time per brain region was 6 minutes 30 seconds, and the total scan time was less than 1 hour.
All spectra were analyzed in the LCModel software package (version 6.3-0D) using a basis set described further in the eAppendix in the Supplement. Spectra were fitted between 0.2 and 4.0 ppm, using baseline correction and macromolecule peaks as described previously.39 Prior to fitting, eddy current correction was performed using the nonsuppressed water signal.
Metabolite levels were calculated relative to the unsuppressed voxel water and are expressed in institutional units (IU, approximately millimolar) as commonly used in MRS studies.20 Metabolite levels were corrected according to cerebrospinal fluid (CSF) content using [X]corrected = [X]/(1 − fCSF), where [X] denotes the metabolite level output by the LCModel, and fCSF denotes the fraction of CSF within the voxel. The value fCSF, as well as the fractions of the gray and white matter, were calculated by segmentation of the anatomical T1-weighted images using the SPM program. No relaxation time corrections were performed.
Metabolite levels were included in further statistical analyses only when their Cramer-Rao lower bounds were below 20%, except for NAAG and lactate where 30% was used owing to their relatively low concentrations. Other measures of spectral quality, namely, the signal to noise ratio (SNR; based on the height of the NAA peak and the SD of the LCModel fit residual) and full width at half maximum (FWHM) were also estimated using the LCModel.
Each participant was administered a comprehensive neuropsychological battery40 of 9 tests spanning 6 cognitive domains described previously.41 Further details about these 6 cognitive domains are included in the eAppendix in the Supplement. Measures were administered and scored according to standard instructions. Finally, a composite cognitive score was calculated as the mean of all 6 individual cognitive domain scores.
Statistical analysis was performed using MATLAB R2017a and RStudio, version 1.0.136. Of the compounds included in the basis set, some of the lower concentration ones were omitted from further analysis because they did not consistently meet the Cramer-Rao lower bounds inclusion criteria, whereas others were also reported as composite compounds since their overlapping resonances led to a certain degree of covariance (Glx = Glu + Gln; tNAA = NAA + NAAG; tCho = phosphocholine + glycerophosphocholine; tCr = creatine + phosphocreatine). In total, therefore, 12 different single or composite compounds per brain region (eTable 1 in the Supplement) were compared between FEP and HC groups using analysis of covariance, including age, self-reported sex, and years of education as covariates. Spectral quality measurements (SNR and FWHM) were also compared between groups using analysis of covariance. Correction for multiple comparisons was performed using the false-discovery rate method, with the desired false-discovery rate to 0.05 (which means that 5% of statistically significant results may be false positives), and the threshold for significance was set to P < .05.
Post hoc correlations were performed between localized metabolite levels and scores of composite neuropsychological performances as well as the individual cognitive domain scores for both FEP and HC groups separately, including age, sex, years of education, and regional CSF content as covariates. Exploratory hypotheses were that performance on neuropsychological tests would correlate with levels of the neuroaxonal/neurotransmitter metabolites that showed significant differences between groups. Again, the false-discovery rate method was applied to correct for multiple comparisons.
Clinical and demographic information is provided in the Table. In total, 81 participants with FEP (mean [SD] age, 22.3 [4.4] years; 57 men) and 91 HC participants (mean [SD] age, 23.3 [3.9] years; 42 men) were enrolled. The composition of the FEP and HC groups differed in sex, years of education, tobacco smoking, and cannabis use. Patients with FEP had significantly lower scores on all neuropsychological test performance measures.
Example 7-T spectra and LCModel fits from the ACC, CSO, and DLPFC in one participant are shown in Figure 1. Cerebrospinal fluid–corrected metabolite levels from the LCModel analysis in all 5 brain regions for both the FEP and HC groups are given in eTable 1 in the Supplement. The concentrations for the metabolites of interest selected for analysis of covariance are presented graphically (Figure 2). Within the ACC, levels of multiple metabolites, including Glu (F1,162 = 8.63, P = .02), NAA (F1,161 = 5.93, P = .03), GABA (F1,163 = 6.38, P = .03), and GSH (F1,162 = 4.79, P = .04), were lower in participants with FEP than in HCs (all P values were corrected for multiple comparisons). The levels of NAA were also significantly lower in patients with FEP in the OFR (F1,136 = 7.23, P = .05) and thalamus (F1,133 = 6.78, P = .03) compared with those levels in HCs. Thalamic GSH levels were also found to be lower in patients with FEP than in HCs (F1,135 = 7.57, P = .03).
Mean MRS voxel tissue compositions (fraction gray matter, white matter, and CSF) are shown in Figure 3 for the FEP and HC groups; no significant differences in voxel composition were found between groups in any location. Spectral quality measurements for each brain region and group are given in eTable 2 in the Supplement. No significant between-group differences in spectral quality were found, except for lower SNR (P = .03) and higher FWHM (P = .003) in the thalamus in the FEP group. The lower thalamic SNR (based on the peak height of NAA) is consistent with the NAA signal being significantly lower in FEP compared to HC.
Among patients with FEP, positive correlations were found between neuropsychological measures and selected metabolites. Correlation coefficients and associated P values are provided in eTable 3 in the Supplement. In the FEP group, composite cognitive score correlated with NAA in the CSO (r = 0.38, P = .01). Scores in the domain of executive function correlated with Glu in the CSO (r = 0.33, P = .04) as well as with GABA in the thalamus (r = −0.36, P = .04). Visual memory scores correlated with Glu (r = 0.30, P = .04) and NAA (r = 0.33, P = .04) in the CSO, as well as with Glu in DLPFC (r = 0.34, P = .02). The levels of NAA in the CSO were also significantly correlated with processing speed (r = 0.48, P < .001) and attention/ working memory (r = 0.38, P = .01). In the ACC, verbal memory correlated with Glu (r = 0.30, P = .03) and GSH (r = 0.30, P = .03). By contrast, among the HC participants, few neuropsychological measures correlated with regional metabolite levels. The levels of GABA in the DLPFC correlated with the composite cognitive score (r = 0.30, P = .03) and with executive functioning (r = 0.30, P = .02), while GSH in the DLPFC negatively correlated with executive functioning (r = −0.28, P = .02).
The principal findings of the present study were lower levels of NAA (better separated from NAAG than at lower field strengths) in the ACC, OFR, and thalamus as well as lower GSH in the ACC and thalamus. In addition, levels of the neurotransmitters GABA and Glu were also lower in the ACC in participants with FEP. These findings suggest that multiple metabolic abnormalities are present in FEP, with the ACC being a primary region of involvement.
The finding of significantly reduced NAA in FEP in the ACC, OFR, and thalamus is consistent with many prior studies (both at 7 T and lower field strengths)21,42,43 that have found reduced tNAA. The NAA levels in the CSO and DLPFC were also lower in FEP although this difference was not statistically significant after correction for multiple comparisons; collectively, these data suggest that NAA is decreased in multiple brain regions; in the present study, significant reductions were found in 3 of 5 brain regions covered by MRS. Reduction of NAA may be interpreted at least in part because of neuronal dysfunction.44,45N-acetylaspartate is also involved in mitochondrial homeostasis.46 Lower NAA in living patients may be ultimately reflected in the synaptic and mitochondrial deficits found in postmortem brains.47 The use of 7-T MRS allows the separation of NAA from NAAG with good precision, and the present study confirmed significant decreases in NAA only, with no significant differences in NAAG after false-discovery rate correction.
The neurotransmitters Glu and GABA are of major interest in psychotic disorders.1,3,11,48,49 Glutamate in schizophrenia/psychosis has been extensively studied3,11 although older studies from lower field strengths tend to report a combined Glu + Gln signal (referred to as Glx). Some studies50,51 have found elevated Glu in early or untreated schizophrenia, while other studies3,11 have found decreased levels, more often in the chronic stages of the disease. Although we do not exclude the possibility that the decrease observed here is influenced by treatment, it may also represent abnormal regional glutamatergic metabolism in psychosis.20 Consistent with the 1 other prior 7-T study with FEP (21 patients and 21 controls),20 Gln levels in the ACC showed no differences between patients and controls, while Glu was significantly lower. In the present study, GABA was found to be lower in the ACC in the FEP group. A recent meta-analysis of GABA measurements in the human brain using MRS concluded that, at present, no consistent alterations in schizophrenia are found, although the data from animal models and postmortem brains have frequently indicated dysfunctional GABA signaling.52
Glutathione is a major antioxidant in the brain and body, and many studies with peripheral tissues from patients with psychosis and animal models have indicated its implication in the pathology of psychosis.53-57 Decreased levels of GSH may underlie excess oxidative stress, which may lead to dysfunction of neurons, in particular GABAergic neurons that are more sensitive to oxidative stress, and excitatory-inhibitory imbalance of neural networks.57-61 Nevertheless, because it has a relatively small and overlapping signal in the MR spectrum, relatively few prior studies have reported in vivo GSH levels in schizophrenia to date and their data have been inconsistent.11,62,63 Glutathione is much better estimated at 7 T than at lower field strengths, and the inconsistent results among the previous reports, at least in part, might come from most of the studies conducted at lower field strength.63 In the present study at 7 T, GSH was significantly lower in FEP than controls in both ACC and thalamus, lending support to the concept that central nervous system oxidative stress plays an important role in the pathophysiology of FEP. Sulforaphane, a natural compound with antioxidant properties, has been reported to reduce cognitive deficits in mental conditions.64 A recent study indicated that 1-week administration of sulforaphane increased peripheral GSH, which also correlated with the upregulation of thalamic GSH measured by 7-T MRS.65
Cognitive deficits in schizophrenia and FEP have been widely reported,66,67 and in the present study, participants with FEP performed significantly worse across all domains tested (Table). Furthermore, the brain MRS measures, such as NAA, Glu, GABA, and GSH, showed a number of significant correlations with the severity of cognitive deficits (eTable 3 in the Supplement). The strongest correlation was found between CSO NAA and processing speed in patients with FEP, rather than in HCs, implying involvement of white matter in the early stage of psychosis (eFigure in the Supplement). These data suggest that these molecular changes are likely to play primary roles in the pathophysiology, rather than secondary or compensatory outcomes. Overall, these correlations lend support to the hypothesis that brain metabolite levels could be useful outcome measures in future treatment trials related to cognition.
While 7-T MRS offers improved SNRs, increased spectral dispersion, and lower Cramer-Rao lower bounds values than at 3 T,10-12 these improvements are only realized if careful attention is applied to experimental details. In particular, high-order shimming and localized power optimization was used in the present study to minimize B0 field inhomogeneity and ensure accurate radiofrequency pulse calibration, respectively. In addition, since metabolite T2’s decrease with increasing field strength, a short echo time STEAM sequence was used to minimize signal loss due to both T2 relaxation and J modulation effects.
The present study was limited by inclusion of patients on antipsychotic medication and other compounds, which may possibly influence results (as discussed above).50,68,69 In particular, tobacco smoking and cannabis use were not matched between groups, with a much higher prevalence in the FEP group, and the study lacked statistical power to covary for this. Consistent with prior studies, the FEP group had a greater prevalence of male participants and a mean of 1 year less education; however, these factors are considered less likely to significantly affect brain metabolite levels.70 Age, sex, and years of education were considered as covariates in the analysis of covariance tests.
The metabolic changes observed are subtle and hence place stringent demands on spectral quantitation techniques. In general, MRS data are expressed relative to either the water or tCr signal from the same voxel (ie, internal reference), and a priori there is no particular reason to expect either of those signals to be unchanged in pathological states. However, in the present study, the tCr to water ratio (eTable 1 in the Supplement) was not significantly different between FEP and controls in any brain region; thus, we do not believe that the choice of reference significantly influenced results in the present study.
Finally, as given in eTable 2 in the Supplement, spectral quality measures vary by location in 7-T MRS (as they also do at 3 T or 1.5 T),71 largely depending on local magnetic susceptibility effects within the head. Therefore, the ability to detect changes in specific brain regions is influenced by location. In the present study, the OFR and thalamic voxels had lower spectral quality (lower SNR and greater linewidths) than the ACC, CSO and DLPFC locations due to more caudal locations as well as possibly due to higher iron content in the thalamus. Hence, subtle metabolic changes are more likely to be detected in the more superior brain regions. However, spectral quality measures were very similar for both patients with FEP and HC participants and thus did not bias between-group comparisons.
In this study of 172 participants, 7-T MRS indicated multiple metabolic abnormalities in patients with FEP compared with healthy participants and also correlated with performance on selected neuropsychological tests. These 7-T MRS findings may shed some light on the pathogenesis of FEP.
Accepted for Publication: August 29, 2018.
Corresponding Authors: Akira Sawa, MD, PhD, Department of Psychiatry and Behavioral Sciences (firstname.lastname@example.org), and Peter B. Barker, DPhil, Russell H. Morgan Department of Radiology and Radiological Sciences (email@example.com), Johns Hopkins University School of Medicine, 600 N Wolfe St, Baltimore, MD 21287.
Published Online: January 9, 2019. doi:10.1001/jamapsychiatry.2018.3637
Author Contributions: Drs Sawa and Barker had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.
Concept and design: Sedlak, Schretlen, Sawa, Barker.
Acquisition, analysis, or interpretation of data: All authors.
Drafting of the manuscript: Wang, Coughlin, DuBois, Sawa, Barker.
Critical revision of the manuscript for important intellectual content: All authors.
Statistical analysis: Wang, Crawford, Schretlen, Sawa.
Obtained funding: Sawa.
Administrative, technical, or material support: Pradhan, Trivedi, DuBois, Sedlak, F. Nucifora, L. Nucifora, Sawa, Barker.
Supervision: Pradhan, Nestadt, Schretlen, Sawa, Barker.
Conflict of Interest Disclosures: Dr Schretlen reported receiving royalties on sales of a test used in the present study under an agreement with Psychological Assessment Resources, Inc, which has been reviewed and approved by Johns Hopkins University in accordance with its conflict of interest policies. No other disclosures were reported.
Funding/Support: This work was supported by grants MH-094268, MH-092443 Silvio O. Conte Center, MH-105660, and MH-107730 from the National Institute of Mental Health and by awards from the Stanley Foundation and S/R Foundation (Dr Sawa); and by grant EB015909 from the National Institute of Biomedical Imaging and Bioengineering and grant MH-096263 from the National Institute of Mental Health (Dr Barker). Participant recruitment was partially supported by the Mitsubishi Tanabe Pharma Corporation.
Role of the Funder/Sponsor: The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; or the decision to submit the manuscript for publication.
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