Proton magnetic resonance spectroscopy in subjects with high genetic risk of schizophrenia: Investigation of anterior cingulate, dorsolateral prefrontal cortex and thalamus

Schizophrenia Research 111 (2009) 86–93

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Schizophrenia Research j o u r n a l h o m e p a g e : w w w. e l s e v i e r. c o m / l o c a t e / s c h r e s

Proton magnetic resonance spectroscopy in subjects with high genetic risk of schizophrenia: Investigation of anterior cingulate, dorsolateral prefrontal cortex and thalamus So Young Yoo a, Suran Yeon b, Chi-Hoon Choi c, Do-Hyung Kang a, Jong-Min Lee b, Na Young Shin d, Wi Hoon Jung d, Jung-Seok Choi a, Dong-Pyo Jang b, Jun Soo Kwon a,d,⁎ a b c d

Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea Department of Biomedical Engineering, Hanyang University, Seoul, Republic of Korea Department of Radiology, National Medical Center, Seoul, Republic of Korea Interdisciplinary Program in Cognitive and Brain Science, Seoul National University, Seoul, Republic of Korea

a r t i c l e

i n f o

Article history: Received 16 November 2008 Received in revised form 21 March 2009 Accepted 21 March 2009 Key words: Magnetic resonance spectroscopy Schizophrenia High genetic risk

a b s t r a c t Objective: Reduced N-acetylaspartate levels in regions of the frontal cortex, including the anterior cingulate cortex, dorsolateral prefrontal cortex, and thalamus, involved in the pathophysiology of schizophrenia suggest that brain metabolite abnormalities may be a marker of genetic vulnerability to schizophrenia. We used proton magnetic resonance spectroscopy (H-MRS) to acquire absolute concentrations of brain metabolites in subjects with a high genetic risk of schizophrenia to investigate the potential relationship between unexpressed genetic liability to schizophrenia and neuronal dysfunction. Method: Included in the study were 22 subjects who had at least two relatives with schizophrenia (high genetic risk group) and 22 controls with no second-degree relatives with schizophrenia. Absolute concentrations of N-acetylaspartate, creatine, choline, glutamate/ glutamine, and myo-inositol and the ratios of metabolites in the anterior cingulate cortex, left dorsolateral prefrontal cortex, and left thalamus were measured using H-MRS at 1.5 Tesla. Results: Relative to the controls, the high genetic risk group showed significant differences in absolute metabolite levels in the spectra of the regions of the left thalamus, including significant decreases in N-acetylaspartate, creatine, and choline concentrations. Conclusions: The study points to neuronal dysfunction, and in particular thalamic dysfunction, as a key region of the vulnerability marker of schizophrenia. Further studies should examine the nature of the thalamus more intensively to further our understanding of thalamic dysfunction as a vulnerability marker. © 2009 Elsevier B.V. All rights reserved.

1. Introduction The identification of vulnerability markers of schizophrenia is necessary for the prevention of the onset of illness or for early treatment prior to the onset of frank illness. High genetic risk (HGR) studies that have investigated unaffected young relatives of individuals with schizophrenia have re-

⁎ Corresponding author. Department of Psychiatry, Seoul National University College of Medicine 28 Yeongon-dong, Chongno-gu, Seoul, Republic of Korea. 110-744. Tel.: +82 2 2072 2972; fax: +82 2 747 9063. E-mail address: [email protected] (J.S. Kwon). 0920-9964/$ – see front matter © 2009 Elsevier B.V. All rights reserved. doi:10.1016/j.schres.2009.03.036

vealed abnormalities in various neuropsychological, brain structural, and functional domains prior to the onset of schizophrenia (Keshavan et al., 2005; Whalley et al., 2005). Young HGR relatives show similar neuropsychological deficits or impairments of attention, executive function, and working memory to those seen in adult probands (Brewer et al., 2005; Johnstone et al., 2002). We previously reported that HGR subjects show a trend of impairment in the affective domain (Lee et al., 2008). Several brain structural studies of young HGR relatives have reported smaller volumes in the amygdalehippocampal complex and thalamus than controls (Keshavan et al., 1997; Lawrie et al., 1999, 2001) and lower gray matter

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density in the anterior cingulate cortex (ACC) (Job et al., 2003). Decreased cortical folding has also been found in young HGR relatives (Jou et al., 2005). However, findings on these brain abnormalities have been inconsistent, as one study has revealed no volumetric deviations except for enlarged lateral ventricles in unaffected relatives of patients with schizophrenia (McDonald et al., 2006). Magnetic resonance spectroscopy (MRS) is an MR technique that assesses the concentrations of various brain metabolites in vivo. It can give more detailed information about neuronal abnormalities at the cellular and metabolic levels than relatively gross volumetric estimates. N-acetylaspartate (NAA) is a metabolite of particular interest in the study of schizophrenia and is a marker of neuronal integrity (Urenjak et al., 1993); it is reduced in conditions in which there is persistent or reversible neuronal loss. Creatine (Cr) represents the cell's energy marker, and choline (Cho) reflects cell membrane turnover. Myo-Inositol (Ins) is a marker of glial cells (Brand et al., 1993). Many 1H-MRS studies have reported some abnormalities in brain metabolites in patients with schizophrenia. Reduced NAA or NAA/Cr has been observed mostly in the frontal cortex including the ACC, dorsolateral prefrontal cortex (DLPFC), thalamus, and temporal lobe, which are particularly involved in schizophrenia (Bertolino and Weinberger, 1999; Cecil et al., 1999; Kegeles et al., 1998; Omori et al., 2000). This suggests that brain metabolite abnormalities may be markers of genetic vulnerability to schizophrenia. Moreover, brain metabolites, especially NAA and NAA/Cr, are related to working memory, another potential vulnerability marker. Two studies of patients with schizophrenia have shown that NAA/Cr levels in the DLPFC predict activation of working memory circuits as measured by positron emission tomography and MR imaging (MRI) (Bertolino et al., 2000; Callicott et al., 2000). Additionally, a correlation between NAA/Cr levels in the prefrontal cortex and performance on a working memory (n-back) task was observed in patients with schizophreniform disorder who had been treated with neuroleptics for less than 2 weeks (Bertolino et al., 2003). In MRS studies of HGR subjects, a trend toward decreased NAA/Cho ratios was observed in the ACCs of young offspring (Keshavan et al., 1997; Keshavan et al., 2003), although these findings must be interpreted with caution because of the small sample sizes. Other studies that have reported decreased NAA/Cr or NAA/Cho in the hippocampuses or frontal lobes of HGR subjects have suggested NAA as a possible intermediate phenotype (Block et al., 2000; Callicott et al., 1998). Tibbo et al. (2004) examined glutamate/glutamine (Glx) concentrations in the frontal lobes of young offspring and suggested that increased Glx concentrations might induce excitotoxicity. However, relative to patients with chronic schizophrenia, MRS findings in first-episode patients and HGR subjects are inconsistent. These inconsistencies may have resulted from methodological differences, subject definition, or volume of interest (VOI) selections. In addition, most MRS studies to date have reported relative ratios such as NAA/Cr or NAA/ Cho. However, the absolute quantification of metabolites is necessary for the proper interpretation of patient data. Ratios use total Cr as an internal standard, and this is acceptable only if Cr remains unchanged under specific pathological conditions. One study reported differences in relative ratios such as

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NAA/Cr, Cho/Cr, and Ins/Cr in depressive patients compared to healthy controls, but examination of absolute concentrations showed differences only in Cr (Gruber et al., 2003). Thus, the use of the ratio might have contributed to some inconsistency in findings among MRS studies. To date, most MRS studies of HGR have focused on regions in the frontal lobe, but the thalamus has been relatively neglected despite the importance of frontal-thalamic circuits in the pathophysiology of schizophrenia. Our aim was to investigate the potential relationship between unexpressed genetic liability to schizophrenia and neuronal dysfunction by using MRS to examine brain metabolite concentrations in the left DLPFC, ACC, and left thalamus of controls and HGR subjects because many previous MRS studies have reported the abnormalities of these regions in patients with schizophrenia or HGR subjects (Block et al., 2000; Theberge et al., 2004). 2. Methods 2.1. Subjects The HGR group consisted of 22 participants who had never had a psychotic disorder but who had at least two relatives with schizophrenia. They were recruited beginning in 2004 through the Seoul Youth Clinic, a center for the prospective, longitudinal investigation of people at high risk for schizophrenia. Potential HGR participants were assessed with the Family Interview for Genetic Studies to investigate their family history of psychiatric disorders and their degree of genetic loading for schizophrenia (Nurnberger et al., 1994). The Comprehensive Assessment At-Risk Mental States (Yung et al., 2002) was used to assess prodromal psychotic symptoms. Among the HGR subjects were those who had at least one firstdegree and at least one second-degree relative with schizophrenia (n = 7), one first-degree and at least one third-degree relative with schizophrenia (n = 7), at least two first-degree relatives with schizophrenia (n = 5), and two affected parents (n = 1) or an affected identical twin (n = 2). The HGR subjects were screened using two instruments: the Positive and Negative Syndrome Scale (PANSS) and the Brief Psychiatric Rating Scale (BPRS). The Hamilton Depression Rating Scale (HAM-D) and the Hamilton Anxiety Rating Scale (HAM-A) were also administered. The Global Assessment of Functioning (GAF) was used to evaluate the overall functioning of a subject. The healthy controls were 22 participants recruited from an internet advertisement and via the social networks of hospital staff members. Controls were gender- and agematched to HGR subjects. Potential controls were excluded if any first- or second-degree biological relatives had a lifetime history of a psychotic disorder. Participants were excluded if they had any lifetime diagnosis of psychotic illness, substance dependence, neurological disease, history of head injury or medical illness with documented cognitive sequelae, or sensory impairment; currently used psychotropic medication; or had an estimated full-scale IQ of less than 70. All HGR and healthy participants were between the ages of 15 and 35. All procedures were carried out in accordance with the current version of the Declaration of Helsinki. The study was approved by the institutional review board at Seoul National University Hospital. After a complete description of the study,

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Fig. 1. Upper: Location of volumes of interest (VOIs) placed in the anterior cingulate gyrus (left), the left dorsolateral prefrontal cortex (middle) and the left thalamus (right). The volumes of the anterior cingulate gyrus, the left dorsolateral prefrontal cortex and the left thalamus are 8 cm3, 6 cm3 and 6 cm3. Lower: Corresponding magnetic resonance spectra, including the LCModel fittings from the anterior cingulate gyrus (left), the left dorsolateral prefrontal cortex (middle) and the left thalamus (right).

all subjects provided written informed consent, and those younger than 18 gave assent in conjunction with informed consent provided by a parent. 2.2. MRS All MRI and MRS experiments were performed using a Siemens 1.5 Tesla system (Avanto, Germany). Foam padding and a forehead-restraint strap were used to limit head movement during the scan. All subjects were advised of the importance of remaining motionless during the procedure. For 1H-MRS volume location and cerebrospinal fluid (CSF) correction of MRS quantification, a single inversion-prepared three-dimensional T1-weighted fast spoiled gradient echo sequence was acquired (TR = 1110 ms, TE = 4.76 ms, matrix 256 × 208, FOV 173 × 230, flip angle = 15°). Other T1 images were acquired for location information of coronal and saggital views (TR = 1020 ms, TE = 4.7 ms, matrix = 256 × 240, FOV = 230 × 230, flip angle = 15°). Spectra comprising 16 water-unsuppressed and 128 watersuppressed averages were acquired using a pointed resolved spin echo spectroscopy pulse sequence (TR = 6000 ms, TE = 140 ms, scan time = 13 min/spectrum) chosen to increase the reliability of Glx in 1.5 Tesla (Jang et al., 2005). The raw data from each acquisition consisted of 2048 points at a

bandwidth of 2500 Hz. The automatic shimming procedure provided by the Siemens system was performed for each scan. The total examination time was approximately 60 min. Three VOIs were obtained from the ACC, left DLPFC, and left thalamus (Fig. 1). A 2 × 2 × 2 cm3 VOI in the ACC was aligned perpendicularly to the tip of the genu corpus callosum and centered at the interhemispheric fissure. The midpoint of the left dorsolateral prefrontal voxel (2 × 1.5 × 2 cm3) was positioned 7.5 mm anterior to the genu of the corpus callosum, and the VOI in the left thalamus was 1.5 × 2 × 2 cm3. Each VOI was carefully located on an axial slice to maximize the gray matter content for homogenous VOI selection by review of saggital and coronal images. 2.3. Postprocessing and data analysis Spectroscopic data were analyzed using LCModel in the range 4.2–1.0 ppm. LCModel has been used for the identification of low-concentration or overlapping metabolites (Provencher, 1993). To ensure that high-quality spectra were obtained, we checked whether the standard deviation of the fitting error of the Glx was less than 25%; if not, we repeatedly acquired MRS data from the region. Absolute quantifications were obtained by repeatedly using a calibration phantom with 50 mM NAA in a 250-cm3

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spherical flask. To obtain the absolute metabolite concentration (Cabs), we multiplied the ratio of the relative concentrations of the in vivo metabolite (Crel, 0) to phantom NAA (Crel. NAA) from LCModel by the absolute concentration of NAA (50 mM) in the phantom as follows: Cabs = 50 mM × ðCrel; 0 = Crel:NAAÞ:

ð1Þ

The segmentation of the MRI data into gray matter, white matter, and CSF components was accomplished using an inhouse software employing a fuzzy C-means algorithm (Yoon et al., 2003). We corrected the metabolite concentrations (C0) for partial volume effects due to CSF by determining the fractional content of the CSF in the VOI (Fcsf) and applying the following correction: C = C0 × ½1 = ð1 − Fcsf Þ:

ð2Þ

The means, standard deviations, and coefficients of variance for NAA, Cr, Cho, Ins, and Glx were obtained. The NAA coefficient of variance of phantom was 3.28%, and the interindividual metabolite coefficients of variance ranged from 6% to 43% (see Table 2). In the ACC, the signal-to-noise ratio was 21.14 (SD = 4.57; range = 14–31) for HGR group and 19.83 (5.27; 13–34) for the controls (t = 0.15, df = 43, p = 0.88). In the DLPFC, it was 16.95 (4.08; 8–26) for the HGR group and 15.9 (2.36; 12–21) for the controls (t = 1.00, df = 43, p = 0.33). In the left thalamus, it was 11.90 (2.36; 7–17) for the HGR group and 12.45 (2.19; 8–16) for the controls (t = −0.76, df = 43, p = 0.45). In the ACC, the full-width half-maximum was 0.068 (0.020; 0.038–0.100) for the HGR group and 0.066 (0.017; 0.038–0.092) for the controls (t = 0.37, df = 43, p = 0.71). In the left DLPFC, it was 0.061 (0.02; 0.038–0.138) for the HGR group and 0.066 (0.013; 0.046–0.107) for the controls (t = −0.88, df = 43, p = 0.39). In the thalamus, it was 0.081 (0.018; 0.054–0.107) for the HGR group and 0.084 (0.024; 0.054–0.153) for the controls (t = −0.43, df = 43, p = 0.67). 2.4. Statistical analysis Demographic information for the groups was compared using chi-squared analyses, t-tests, and one-way analyses of variance. Metabolite parameters were compared between groups using an analysis of covariance (ANCOVA) with age as a covariate in the three regions separately. The significance level was set at p b 0.05. SPSS Version 14.0 (SPSS Inc., Chicago, IL) was used for analyses. Correlations between metabolites and

Table 1 Demographic data of participants. HGR (n = 22)

Age (years) Gender (female/male) GAF PANSS BPRS HAM-D HAM-A

Control (n = 22)

Mean

SD

Mean

SD

T

p

df

22.64 10/12 80.43 35.41 27.76 5.23 3.09

5.28

23.09 9/13 – – – – –

4.84

0.131

0.719

43

10.9 7.71 5.76 7.56 4.82

– – – – –

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Table 2 Absolute Concentrations of the anterior cingulate cortex, left dorsolateral prefrontal cortex and left thalamus. HGR (n = 22) Mean

SD

Control (n = 22)

ANCOVA

CV

Mean

SD

CV

6.6 10.9 14.37 11.32 15.09

10.11 10.63 1.86 5.26 12.09

0.76 0.99 0.23 0.62 1.77

7.52 9.31 12.31 11.87 14.64

0.63 1.09 0.27 0.85 0.27

0.431 0.302 0.605 0.360 0.603

Dorsolateral prefrontal cortex NAA 9.27 2.42 26.05 Cr 7.11 1.79 25.17 Cho 1.40 0.26 18.89 Ins 4.19 1.67 39.90 Glx 8.37 3.39 40.48

9.02 6.66 1.41 3.61 7.41

1.07 1.06 0.28 0.88 2.55

11.83 15.89 19.72 24.26 34.42

0.20 2.58 2.95 2.64 0.86

0.661 0.115 0.093 0.111 0.361

Thalamus NAA 7.56 Cr 5.36 Cho 1.37 Ins 2.61 Glx 5.96

8.50 5.96 1.54 2.72 5.70

0.94 0.66 0.22 0.78 1.60

11.01 11.11 14.35 28.8 28.12

10.87 11.02 7.56 0.21 0.15

0.002 0.001 0.008 0.652 0.697

Anterior cingulate cortex NAA 10.28 0.68 Cr 10.98 1.20 Cho 1.90 0.27 Ins 5.44 0.62 Glx 12.38 1.87

0.97 0.54 0.17 0.85 2.51

12.78 10.11 12.62 32.52 42.14

F

P

HGR, High Genetic Risk group; SD, standard deviation; CV, Coefficients of variance: (SD/mean) × 100.

symptoms were evaluated with the Pearson product-moment correlation coefficient.

3. Results Table 1 shows the demographic and clinical data for the participants. The groups did not differ significantly in age. Table 3 Relative ratios of the anterior cingulate cortex, left dorsolateral prefrontal cortex and left thalamus. HGR (n = 22)

Control (n = 22)

ANCOVA

Mean

SD

Mean

SD

F

P

0.08 0.02 0.05 0.16 0.66 0.47 1.21

1.12 0.2 0.58 1.13 5.51 2.86 5.61

0.09 0.02 0.05 0.11 0.65 0.38 0.87

0.05 0.06 0.59 0.04 0.00 0.13 0.01

0.817 0.800 0.447 0.837 0.963 0.715 0.927

Dorsolateral prefrontal cortex NAA/Cr 1.30 0.23 Cho/Cr 0.20 0.03 Ins/Cr 0.58 0.23 Glx/Cr 1.17 0.31 NAA/Cho 6.61 1.44 Ins/Cho 2.92 1.19 Glx/Cho 3.87 2.93

1.37 0.2 0.55 1.10 7.02 2.83 4.54

0.13 0.03 0.13 0.39 1.10 0.84 2.96

2.56 0.03 0.23 0.25 2.44 0.07 0.56

0.117 0.858 0.633 0.618 0.125 0.789 0.458

Thalamus NAA/Cr Cho/Cr Ins/Cr Glx/Cr NAA/Cho Ins/Cho Glx/Cho

1.44 0.26 0.46 0.95 5.59 1.78 4.23

0.11 0.02 0.13 0.23 0.58 0.45 1.98

0.30 0.04 0.43 2.08 0.08 0.68 1.72

0.589 0.839 0.515 0.156 0.784 0.413 0.196

Anterior cingulate cortex NAA/Cr 1.12 Cho/Cr 0.21 Ins/Cr 0.59 Glx/Cr 1.14 NAA/Cho 5.5 Ins/Cho 2.91 Glx/Cho 5.64

1.41 0.26 0.49 1.14 5.54 1.91 0.26

0.15 0.03 0.16 0.55 0.66 0.63 0.03

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Three HGR subjects had experienced subthreshold attenuated psychotic symptoms. There was no significant difference in age between subjects with and without prodromal symptoms. The absolute values for NAA, Cr, Cho, Ins, and Glx for the two groups are shown in Table 2. Relative to the controls, the HGR subjects showed significant differences in metabolite levels in the spectra of the regions of the left thalamus, including significant decreases in NAA, Cr, and Cho concentrations (Table 2, Fig. 2). In additional comparisons of only the subjects without prodromal symptoms to healthy controls, significant differences were maintained. However, the relative concentrations of these metabolites were not different between the two groups (Table 3). We didn't find any correlations between metabolites and symptoms in the HGR subjects. 4. Discussion We evaluated whether brain metabolites in vivo are associated with a possible genetic vulnerability to schizophrenia. To our knowledge, this is the first 1H-MRS study investigating absolute concentrations and ratios of brain metabolites simultaneously in high genetic risk subjects for schizophrenia. We found that absolute concentrations of NAA, Cr, and Cho were significantly reduced in the left thalamuses of HGR subjects compared to controls, but we observed no differences in metabolite concentrations in the left DLPFCs or the ACCs. These findings were supported by an additional analysis that excluded three subjects with prodromal symptoms. It is noteworthy that significant differences in metabolite concentrations were observed only in the thalamus of the HGR group. The most of MRS studies with patients or at-risk subjects with schizophrenia have found the abnormalities of the metabolic ratios, such as NAA/Cr, NAA/Cho or Cho/Cr in the frontal lobe (Cecil et al., 1999; Wood et al., 2003; Jenssen et al., 2006). The thalamus transmits sensory and motor information to the brain cortex; it is associated with the frontal lobe and basal ganglia, which are involved in cognitive pro-

cessing, such as sensory information processing, memory, and concentration (Blennow et al., 2000; Gaser et al., 2004). Studies have shown that the thalamus plays an important role in the pathophysiology of schizophrenia. Significant abnormalities of the thalamus, including reduced glucose metabolism (Hazlett et al., 2004), decreased volume (Cahn et al., 2002; Gaser et al., 2004), and synaptic degeneration (Blennow et al., 2000), have been observed in many neuroimaging studies of schizophrenia. In addition, thalamic volume is correlated with symptom severity (Preuss et al., 2005). However, accumulating evidence suggests that these thalamic abnormalities might not represent neurodegenerative change occurring after the onset of illness. Even in the early phase of schizophrenia, a reduction in thalamic volume has consistently been observed (Arnold et al., 2001; Bjartmar et al., 2002; Seidman et al., 1999; Tsai and Coyle, 1995). Moreover, HGR subjects show a reduction in thalamic volume (Staal et al., 1998), especially of the left thalamus (Lawrie et al., 2001; Lymer et al., 2006; McIntosh et al., 2004; Seidman et al., 1999). According to Harms et al. (2007), thalamic shape abnormalities are observed in siblings of patients with schizophrenia as well as in schizophrenia probands, suggesting that shape deformation of the thalamus represents a potential neuroanatomical endophenotype of schizophrenia. Based on these findings, structural or functional abnormalities of the thalamus may be correlates of vulnerability markers of schizophrenia. NAA is synthesized in the neuronal mitochondria and is localized primarily in neurons (Urenjak et al., 1993). The several functions have been proposed for NAA, such as an important cellular osmolyte, a molecular water pump, intercellular signaling and participation in oligodendrocyte myelin formation (Baslow, 2003). NAA diminishes with axonal loss (Bjartmar et al., 2002), and there is some evidence linking spectroscopically measured NAA to neuronal integrity in a wide range of disorders (Arnold et al., 2001; Tsai and Coyle, 1995). In patients with schizophrenia, NAA reductions may represent volume reductions (in other words, neuronal loss).

Fig. 2. Absolute metabolite concentrations in the thalamus of subjects with high genetic risk of schizophrenia (n = 22) and comparison subjects (n = 22). NAA, N-acetylaspartate; Cho, Choline; Cr, Creatine; Glx, Glutamate/Glutamine; Ins, Myo-Inositol. ⁎ Significant difference between subjects with high genetic risk and comparison subjects (p b 0.05, df = 43, ANCOVA with least significant difference post hoc test).

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Our finding of NAA reduction in the thalamus may also have resulted from thalamic volume reduction, but further study is needed to confirm this. The NAA reduction found here may represent thalamic dysfunction. Functional neuroimaging studies and electrophysiological studies have shown that thalamic dysfunction may be responsible for impairments in cognitive function and sensory processing in schizophrenia (Braff, 1993; Buchsbaum et al., 1996; Crespo-Facorro et al., 1999). In addition, NAA reduction may reflect metabolic deficits in neuronal mitochondria. The production rate of spectroscopically visible NAA is related to the utilization rate of cerebral glucose (Bertolino et al., 2003; Moreno et al., 2001). Diminished mitochondrial energy production may follow reduced neuronal energy demand due to synaptic dysfunction or loss, and there is some evidence for synaptic dysfunction or loss in the mediodorsal and anterior thalamic nuclei in patients with schizophrenia (Blennow et al., 2000). The reductions in Cr found here also support the possibility of metabolic reduction in the thalamus of HGR subjects. The Cr peak is made up of contributions from both Cr and phosphocreatine. In states of increased metabolite demand, phosphocreatine is converted to Cr. The hypermetabolic state results in an increase in the total Cr resonance peak. Conversely, increased amounts of phosphocreatine compared to Cr, seen in cases of hypometabolism, produce a lower total Cr resonance peak. According to Wood et al. (2003), there is a significant elevation of the NAA/Cr and Cho/Cr ratios in the DLPFCs of ultra-high-risk subjects for schizophrenia. The authors speculated that elevated ratios of NAA/Cr and Cho/ Cr might be indicative of hypometabolism of Cr in subjects before the onset of psychosis. Therefore, it is possible that our HGR group may have been experiencing hypometabolism in the left thalamus. We also found decreased levels of Cho in HGR relatives. The main component of the Cho signal is related to Chocontaining cell membrane phospholipids, and a reduction in the Cho signal has been attributed to an overall reduction in the synthesis of Cho-containing phospholipids. Findings regarding Cho and the Cho/Cr ratio among patients with schizophrenia have been inconsistent. Some studies have reported no differences (Bertolino et al., 1996; Heimberg et al., 1998), whereas others have reported decreased levels of Cho or Cho/Cr (Omori et al., 2000). Increased levels of Cho or Cho/Cr have also been found (Auer et al., 2001), especially in drug-naïve patients (Bustillo et al., 2002), and the concentration of Cho is positively correlated with the duration of untreated psychosis (Theberge et al., 2004), suggesting that Cho is a potential marker for disease activity. In a study of high-risk patients, Jessen et al. (2006) observed increased Cho in the ACCs of at-risk subjects who converted to schizophrenia compared to those who did not convert. In contrast, our findings of decreased Cho suggest a decreased turnover of cell membrane that may be related to hypometabolism or dysfunction in the left thalamus of HGR subjects. Most MRS studies to date have reported relative ratios such as NAA/Cr or NAA/Cho. However, we observed significant differences in metabolites only in absolute concentrations, not relative ratios. Absolute quantification, rather than the acquisition of metabolite ratios, increases the reliability of MRS measurements (Pfefferbaum et al., 1999). We had no need to consider the effects of other metabolites when interpreting decreased NAA, Cr, and

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Cho. Many studies have observed ratios of metabolites using total Cr as an internal standard. Given that the absolute concentration of Cr was altered in the HGR subjects compared to the controls in this study, the use of one internal standard may not have been appropriate. Had we measured only the relative concentrations of metabolites, we would not have detected the significant differences between the two groups. This study has a technical limitation that must be considered. Each single voxel contained only a partial area within the ACC, DLPFC, or thalamus. Studies that have reported frontal abnormalities in HGR have examined whole regions, not just parts, of the frontal lobe. Thus, we cannot exclude neuronal dysfunction of the frontal area. However, given that the reduction of NAA in the frontal lobe was consistent with findings for schizophrenia (Steen et al., 2005) and at-risk subjects (Jessen et al., 2006; Wood et al., 2003), and that such a reduction was not found in the healthy relatives of the patients with schizophrenia, we speculate that the reduction of NAA in the frontal lobe might be associated with symptoms of schizophrenia or a “state marker.” Recent study reported no difference of Glx in high-risk subjects in the medial frontal lobe using 3 T MRS although the high glutamate group contained a larger proportion of high-risk than healthy volunteers subjects (Purdon et al., 2008). In summary, this study points to neuronal dysfunction, and in particular thalamic dysfunction, as a key region of the vulnerability marker of schizophrenia. Future studies should examine the nature of the thalamus more intensively to further the understanding of thalamic dysfunction as a vulnerability marker of schizophrenia. Role of funding source The Ministry of Science and Technology of the Republic of Korea and Seoul National University Hospital had no further role in the study design; in the collection, analysis and interpretation of data; in the writing of the report; and in the decision to submit the paper for publication. Contributors So Young Yoo wrote the draft of the manuscript and performed data collection and the analysis. Suran Yeon participated in MRS acquisition, pre-processing and analysis, and assisted with interpretation of study findings. Chi-Hoon Choi aided in MRI data collection and supervised the MR scanning. Do-Hyung Kang recruited subjects, undertook clinical assessments of the participants and substantially contributed in writing the manuscript. Jong-Min Lee assisted with interpretation of study findings and supervised the MRS analysis. Na Young Shin administered a neuropsychological test battery to the subjects who participated in this study. Wi Hoon Jung aided in MRI data collection. Jung-Seok Choi completed a screening interview for the subjects of this study. Dong-Pyo Jang aided in initial MRS data collection and supervised the MR scanning. Jun Soo Kwon undertook the study design and managed the whole procedure of this study. All authors contributed to and have approved the final manuscript.

Conflict of interest None of the authors have any conflict of interests to this study. Acknowledgements This work was supported by a Research fund (2008) from Seoul National University Hospital and a grant (M103KV010007 04K2201 00710) from Brain Research Center of the 21st Century Research Program funded by the Ministry of Science and Technology of Republic of Korea.

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