Associations of hippocampal metabolism and regional brain grey matter in neuroleptic-naïve ultra-high-risk subjects and first-episode schizophrenia

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Abstract

Hippocampal pathology has been shown to be central to the pathophysiology of schizophrenia and a putative risk marker for developing psychosis. We applied both 1H MRS (proton magnetic resonance spectroscopy) at 3 Tesla and voxel-based morphometry (VBM) of high-resolution brain structural images in order to study the association of the metabolites glutamate (Glu) and N-acetyl-aspartate (NAA) in the hippocampus with whole-brain morphometry in 31 persons at ultra-high-risk for psychosis (UHR), 18 first-episode schizophrenia patients (Sz), and 42 healthy controls (all subjects being neuroleptic-naïve). Significantly diverging associations emerged for UHR subjects hippocampal glutamate showed positive correlation with the left superior frontal cortex, not seen in Sz or controls, while in first-episode schizophrenia patients a negative correlation was significant between glutamate and a left prefrontal area. For NAA, we observed different associations for left prefrontal and caudate clusters bilaterally for both high-risk and first-episode schizophrenia subjects, diverging from the pattern seen in healthy subjects. Our results suggest that associations of hippocampal metabolites in key areas of schizophrenia might vary due to liability to or onset of the disorder.

Introduction

The high-risk state for psychosis has become a major paradigm in schizophrenia research that is relevant for both early clinical intervention as well as the study of the biological basis of schizophrenia (Fusar-Poli et al., 2013). Subjects at ultra-high risk (UHR) of developing psychosis show a number of cognitive as well as brain structural and functional changes similar to those seen in schizophrenia (Cooper et al., 2014, Fusar-Poli, 2012, Palaniyappan et al., 2012). These alterations reflect, to differing extent, the contribution of genetic risk or liability, changes seen in the prodrome, and changes at the onset of schizophrenia (Jung et al., 2012).

The hippocampus has been of particular interest for UHR studies, since it is central to the pathophysiology of schizophrenia, especially in the context of glutamatergic dysfunction (Tamminga et al., 2012). Structural changes of the hippocampus have been demonstrated with magnetic resonance imaging (MRI) in both first-episode and chronic populations (Adriano et al., 2012), and multi-modal imaging has revealed multiple abnormal hippocampal markers in UHR subjects (Wood et al., 2010).

Magnetic resonance spectroscopy (MRS) has increasingly been used to assess metabolic changes in UHR subjects and during transition to psychosis, as it provides additional information about specific metabolites, such as glutamate (Glu), or markers of neuronal integrity, such as N-Acetyl-aspartate (NAA). There is some evidence that NAA is decreased in the hippocampus in schizophrenia (Steen et al., 2005), although there have been conflicting results (He et al., 2012), and the influence of several aspects, like chronicity of disease or medication, needs further evaluation. However, the pathophysiological process accompanying changes of Glu and/or NAA in the hippocampus in emerging psychosis might not only include changes in the level of these metabolites, but more importantly also changes in their effects on functional parameters and connectivity with other key regions of schizophrenia pathophysiology, and/or on remote neural network. This has been suggested by a number of recent studies that combined MRS with other structural and/or functional imaging techniques. Kraguljac and colleagues reported that the association between NAA and Glu concentrations in the hippocampus (as seen in healthy controls) was lost in a large sample of schizophrenia patients, indicating a decoupling of these physiologically interrelated metabolites (Kraguljac et al., 2012). In a subsequent study, the same group also identified a correlation between NAA and combined glutamate and glutamine markers with hippocampal volume in unmedicated Sz patients (Kraguljac et al., 2013). Abnormal levels of hippocampal metabolites, however, also appear to influence remote areas, as seen in diverging correlation patterns between hippocampal NAA and prefrontal activation measured with functional MRI (Hutcheson et al., 2012).

In UHR subjects with at-risk mental state (ARMS), a series of recent studies has suggested that hippocampal glutamate changes might lead to a number of structural and functional changes in interconnected networks (Egerton et al., 2012). Hippocampal glutamate was correlated with striatal [18F]-DOPA uptake, an indicator of striatal dopamine turnover, and a putative indicator of transition to psychosis (Stone et al., 2010). Also, the physiological association between hippocampal glutamate and medial temporal brain activation seen in healthy subjects was lost in UHR subjects with ARMS status (Valli et al., 2011). Currently, it is unclear whether the loss of such associations (studied as correlations between two structural/functional markers) is related to liability or to transitional processes towards the onset of psychosis.

Against the background of these findings, we investigated the relation between the metabolic markers glutamate and NAA in the hippocampus with brain structure (i.e. morphometry) for three different groups: UHR subjects identified in an early psychosis programme, patients with first-episode schizophrenia, and healthy controls. We tested the hypothesis that correlations between hippocampal Glu and/or NAA with other key brain regions implicated in previous studies, i.e. the lateral prefrontal cortex, anterior cingulate cortex, thalamus, and the hippocampus itself, would show a group effect indicating that associations are different depending on risk vs. actual onset of schizophrenia. In order to avoid confounding effects of medication, which have been shown in previous MRS studies on Glu (Poels et al., 2014), we only included subjects who were neuroleptic-naïve, i.e. had never been treated with antipsychotics.

Section snippets

Subjects

We included in this study a total of 91 subjects: 31 persons at ultra-high-risk (UHR) of developing psychosis, 18 patients with first-onset schizophrenia (Sz), and 42 healthy control subjects. Demographic details are given in Table 1. Groups did not differ in age (ANOVA: F=0.211; p=0.81) or gender composition (Chi-square-test: p=0.525). All study participants provided written informed consent to a study protocol, which had been approved by the Ethics Committee of Jena University Medical School

Hippocampal Glu and NAA levels

For the studied four metabolic markers, group effect (ANOVA) reached significance for NAA in the right hippocampus (F=3.16; p=0.047), whereas post-hoc Tamhane׳s T2 test revealed a trend (p=0.059) for the healthy control vs. UHR comparison. For the additional repeated measures ANOVA, we found no effect for either hemisphere (F=0.084; p=0.773) or a group by hemisphere interaction (F=1.088; p=0.341). Mean Glu and NAA levels are given in Table 2.

Glutamate and brain structural effects

For the VBM analysis with right hippocampal glutamate

Discussion

In this study, we tested the hypothesis of diverging associations of hippocampal metabolic markers (glutamate and NAA) with brain grey matter. We demonstrate that these associations occur in key regions relevant to the pathophysiology of schizophrenia, i.e. striatum and prefrontal cortices, and exhibit different behaviour for the UHR, first-episode schizophrenia, and healthy control groups. While in some areas correlations are similar between UHR and first-episode schizophrenia, only effects in

Role of funding source

This study was partially supported through Grants of German Research Foundation (Deutsche Forschungsgemeinschaft, DFG, Grant Sm 68/3-1, to St.S.). I.N. was supported by a Junior Scientist Grant of the Friedrich-Schiller-University of Jena. (KST 21007087). GPA is supported by a NHMRC Senior Research Fellowship 1080963.

The funding sources had no influence on data collection, analysis, or interpretation of the report, its writing or the decision to submit the paper.

Contributors

I.N., St.S., H.S., and C.G. designed the study and contributed towards its protocol.

M.D., N.S., and St.S. collected data, where H.S. and I.N. contributed to subject recruitment, and consultation by P.McG. and G.P.A in subject selection.

I.N., C.G., J.R.R., A.G., C.G., and St.S. contributed to establishing of image post-processing routines and processing algorithm.

I.N., R.M, S.B., C.L., and C.G. contributed to data analysis.

I.N. wrote the first draft of the manuscript.

All authors contributed to

Conflict of interest

This study was partially supported through grants of German Research Foundation (Deutsche Forschungsgemeinschaft, DFG, Grant Sm 68/3-1, to St.S.). In was supported by a Junior Scientist Grant of the Friedrich-Schiller-University of Jena. (KST 21007087). GPA is supported by a NHMRC Senior Research Fellowship 1080963. Professor McGorry currently receives research support from a National Health and Medical Research Council of Australia and the Colonial Foundation. He has also received grant

Acknowledgements

The authors would like to thank all study participants for their support.

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