Elsevier

NeuroImage

Volume 48, Issue 3, 15 November 2009, Pages 525-531
NeuroImage

MR spectroscopic evaluation of N-acetylaspartate's T2 relaxation time and concentration corroborates white matter abnormalities in schizophrenia

https://doi.org/10.1016/j.neuroimage.2009.06.061Get rights and content

Abstract

Magnetic resonance spectroscopy enables the in vivo analysis of certain aspects of brain biochemistry. Reduced N-acetylaspartate in key regions of schizophrenia has been reported repeatedly but not without controversy. Our objective is to investigate whether reduced N-acetylaspartate concentrations determined without correction for individual T2 relaxation time (referred to as ‘apparent tNAA concentration’) are due to a reduced absolute N-acetylaspartate concentration or to altered relaxation properties. For this purpose we measured absolute concentrations while evaluating individual T2 relaxation times. We evaluated the metabolite concentrations and metabolite/water relaxation times of a frontal white matter voxel from 23 patients who met DSM-IV criteria for schizophrenia and 29 healthy control subjects with similar age at a 3 T magnetic resonance scanner. A significantly reduced N-acetylaspartate concentration as well as shortened N-acetylaspartate's T2 relaxation time in the schizophrenic patient group was found. The apparent N-acetylaspartate concentration difference between healthy controls and patients with schizophrenia increased with the echo time due to a decreased N-acetylaspartate's T2 in the schizophrenic group. No group difference was found for any other metabolite concentration or metabolite/brain water relaxation time. These findings of reduced N-acetylaspartate as well as shortened N-acetylaspartate's T2 relaxation time give further evidence for microstructural white matter changes in schizophrenia. Furthermore, they elucidate why reports of a reduced N-acetylaspartate concentration in schizophrenia were not always corroborated.

Introduction

Convergent evidence from post-mortem (Benes et al., 2001, Flynn et al., 2003, Hof et al., 2002, Katsel et al., 2005a, Rajkowska et al., 1998), genetics data (Hakak et al., 2001, Katsel et al., 2005a, Katsel et al., 2005b, Katsel et al., 2008), and in vivo neuroimaging studies (Ashtari et al., 2007, Bagary et al., 2003, Fields, 2008b, Karlsgodt et al., 2008, Kubicki et al., 2005, Lim et al., 1999, Schlosser et al., 2007) implicates pathological changes in white matter of schizophrenia patients. Specifically, alterations in the density or function of myelin forming cells, oligodendrocytes and/or myelination in patients with schizophrenia (SZ) compared to healthy controls (HC) have been reported (Davis et al., 2003). A decreased number of oligodendrocytes was found in the cortex and thalamic nucleus, and myelin abnormalities or apoptotic oligodendrocytes were seen prefrontally (Fields, 2008a, Tkachev et al., 2007). Preliminary genetic evidence comes from a genome wide expression study that evaluated more than 6000 genes in frontal white matter in patients with SZ. In a total of 89 differentially expressed genes 35 with functional relations to myelination were found (Hakak et al., 2001) (for review see also Fields (2008a)). Importantly, impaired myelination in schizophrenia could contribute to abnormalities of neural connectivity, a central pathophysiological mechanism of the disorder. While the existence of white matter abnormalities in schizophrenia is well established, the underlying cellular biochemistry is still being investigated. An important tool towards this goal is proton magnetic resonance spectroscopy (1H-MRS).

The most consistent finding reported in these studies is a reduced N-acetylaspartate (NAA) concentration in several brain regions in SZ (Steen et al., 2005) including frontal lobe (Deicken et al., 1997a), cortical white matter (Lim et al., 1998), cingulate cortex (Deicken et al., 1997b, Ende et al., 2000, Ende et al., 2005), cerebellar vermis (Deicken et al., 2001, Ende et al., 2005), mediodorsal and anterior thalamus (Ende et al., 2001, Jakary et al., 2005), basal ganglia and hippocampus (Ende et al., 2003). These studies were based on spectra acquired at lower field (< 3 T) and with long echo times (TE > 80 ms). Some other studies conducted at 3 and 4 T and short TE could not replicate these findings (Bartha et al., 1999, Delamillieure et al., 2002, Kegeles et al., 2000) (for review see Steen et al. (2005)). The MR signals decay with increasing TE. This is caused by a relaxation mechanism which is determined by the individual molecules' interaction with its chemical surrounding and can be quantitatively expressed as T2 relaxation time. If concentration differences between groups are detected in long but not in short TE spectra they might originate from altered T2 relaxation in one group. Thus absolute metabolite quantification with individual T2 correction is necessary to distinguish between metabolite concentration differences and T2 relaxation time differences between groups. For example in a study with multiple sclerosis patients the T2 relaxation time of NAA (T2NAA) was found to be altered in multiple sclerosis lesions as well as in normal appearing white matter (Schubert et al., 2002). Thus the reported stronger NAA differences observed at long TE in schizophrenia provokes the question if the T2NAA rather than the NAA concentration itself might be altered in schizophrenic patients.

Therefore, in order to investigate if the metabolite concentrations are altered in SZ the measurement of individual metabolite relaxation times is necessary. The major problem in determining the individual metabolite relaxation time for each subject is the long measurement time since it requires the evaluation of the metabolites signal decay with varying TE. For each spectrum at a particular TE a sufficient signal to noise ratio (SNR) is needed and the more spectra at different TEs are acquired the more precise the T2 estimation will be. Nevertheless, only with the knowledge of the individual relaxation time it is possible to evaluate and compare absolute concentrations without relaxation bias.

In this study we aimed to estimate individual T2 relaxation times and thus absolute metabolite concentrations without relaxation bias of the frontal white matter in schizophrenic patients and to compare these results with healthy control measures. To make this methodological effort possible, we chose a single voxel small enough to encompass almost solely white matter and which is still big enough to yield sufficient signal at longer TE for the estimation of reliable T2 relaxation.

To investigate the relevance of the measured absolute metabolite concentrations for clinical state, we also collected clinical and neuropsychological data for symptom characterization.

Section snippets

Subjects

Following approval by the ethical committee of the Faculty for Medicine Mannheim at the University of Heidelberg, 23 SZ (mean age: 31.7 ± 8.8 years; 15 males) and 29 HC (mean age: 32.5 ± 9.7 years; 12 males) were recruited. Written informed consent was obtained after the purpose of the study and the procedure were explained to all participants.

All patients had been evaluated at the Central Institute of Mental Health and were either unmedicated (N = 12) or treated with atypical antipsychotics in

Results

A series of typical spectra acquired from the left frontal white matter at the different TEs is shown in Fig. 2. There were no significant sex or age differences between the groups. ANCOVA results showed a significant reduction of tNAAabs concentrations in SZ compared to HC [F(1) = 4.141, p = 0.02; Fig. 3]. Furthermore, we found significantly reduced T2tNAA values in SZ [F(1) = 6.873, p = 0.011; Fig. 4].

The spectra acquired at TE = 30 ms showed only a trend for a reduced apparent tNAA concentration tNAATE

Discussion

We observed a significant decrease of the tNAA concentration in frontal white matter in patients with schizophrenia compared to healthy controls using individual T2 relaxation corrected data and a method that allows absolute metabolite values in mM to be quantified with the fully relaxed water signal from the same voxel. Additionally, we determined differences in T2tNAA which we interpret as a sign of altered WM microstructure in SZ. Supporting the validity of our data evaluation age effects in

Acknowledgments

This study was in part funded (PhD stipend for the corresponding author) by the PhD Funding Program of the State of Baden-Wuerttemberg (Landesgraduiertenfoerderung, University of Heidelberg). Parts were presented on April 21, 2009 at the 17th ISMRM, Hawai'i. We thank the physicians Dr. Susanne Englisch, Dr. Christine Esslinger, Dr. Dragos Inta, Dr. Alexander Gutschalk, and Dr. Andrea Weinbrenner from the Department of Psychiatry and Psychotherapy from the Central Institute of Mental Health for

References (57)

  • FieldsR.D.

    White matter in learning, cognition and psychiatric disorders

    Trends Neurosci.

    (2008)
  • JakaryA. et al.

    N-acetylaspartate reductions in the mediodorsal and anterior thalamus in men with schizophrenia verified by tissue volume corrected proton MRSI

    Schizophr. Res.

    (2005)
  • KarlsgodtK.H. et al.

    Diffusion tensor imaging of the superior longitudinal fasciculus and working memory in recent-onset schizophrenia

    Biol. Psychiatry

    (2008)
  • KatselP. et al.

    Variations in differential gene expression patterns across multiple brain regions in schizophrenia

    Schizophr. Res.

    (2005)
  • KatselP. et al.

    Variations in myelin and oligodendrocyte-related gene expression across multiple brain regions in schizophrenia: a gene ontology study

    Schizophr. Res.

    (2005)
  • KegelesL.S. et al.

    Hippocampal pathology in schizophrenia: magnetic resonance imaging and spectroscopy studies

    Psychiatry Res.

    (2000)
  • KubickiM. et al.

    DTI and MTR abnormalities in schizophrenia: analysis of white matter integrity

    NeuroImage

    (2005)
  • OngurD. et al.

    Abnormal glutamatergic neurotransmission and neuronal–glial interactions in acute mania

    Biol. Psychiatry

    (2008)
  • RuschN. et al.

    Neurochemical and structural correlates of executive dysfunction in schizophrenia

    Schizophr. Res.

    (2008)
  • SchlosserR.G. et al.

    White matter abnormalities and brain activation in schizophrenia: a combined DTI and fMRI study

    Schizophr. Res.

    (2007)
  • SchubertF. et al.

    Serial 1H-MRS in relapsing-remitting multiple sclerosis: effects of interferon-beta therapy on absolute metabolite concentrations

    Magma

    (2002)
  • SchubertF. et al.

    Glutamate concentrations in human brain using single voxel proton magnetic resonance spectroscopy at 3 Tesla

    NeuroImage

    (2004)
  • SelemonL.D. et al.

    The reduced neuropil hypothesis: a circuit based model of schizophrenia

    Biol. Psychiatry

    (1999)
  • SoherB.J. et al.

    GAVA: spectral simulation for in vivo MRS applications

    J. Magn. Reson.

    (2007)
  • Weber-FahrW. et al.

    A fully automated method for tissue segmentation and CSF-correction of proton MRSI metabolites corroborates abnormal hippocampal NAA in schizophrenia

    NeuroImage

    (2002)
  • AshtariM. et al.

    Disruption of white matter integrity in the inferior longitudinal fasciculus in adolescents with schizophrenia as revealed by fiber tractography

    Arch. Gen. Psychiatry

    (2007)
  • AydinK. et al.

    Quantitative proton MR spectroscopy findings in the corpus callosum of patients with schizophrenia suggest callosal disconnection

    AJNR Am. J. Neuroradiol.

    (2007)
  • BagaryM.S. et al.

    Gray and white matter brain abnormalities in first-episode schizophrenia inferred from magnetization transfer imaging

    Arch. Gen. Psychiatry

    (2003)
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