Neuro-metabolite profiles of rodent models of psychiatric dysfunctions characterised by MR spectroscopy

Accepted Manuscript Neuro-metabolite profiles of rodent models of psychiatric dysfunctions characterised by MR spectroscopy Sakthivel Sekar, Joanes Grandjean, Joanne FV. Garnell, Roland Willems, Hilde Duytschaever, Sankar Seramani, Huang Su, Luc Ver Donck, Kishore K. Bhakoo PII:

S0028-3908(18)30856-6

DOI:

https://doi.org/10.1016/j.neuropharm.2018.11.021

Reference:

NP 7433

To appear in:

Neuropharmacology

Received Date: 11 June 2018 Revised Date:

12 November 2018

Accepted Date: 13 November 2018

Please cite this article as: Sekar, S., Grandjean, J., Garnell, J.F., Willems, R., Duytschaever, H., Seramani, S., Su, H., Ver Donck, L., Bhakoo, K.K., Neuro-metabolite profiles of rodent models of psychiatric dysfunctions characterised by MR spectroscopy, Neuropharmacology (2018), doi: https:// doi.org/10.1016/j.neuropharm.2018.11.021. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

ACCEPTED MANUSCRIPT

Neuro-metabolite profiles of rodent models of psychiatric

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dysfunctions characterised by MR spectroscopy.

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Sakthivel Sekara#, Joanes Grandjeana#, Joanne FV Garnella, Roland Willemsb, Hilde

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Duytschaeverb, Sankar Seramania, Huang Suc, Luc Ver Donckb, Kishore K Bhakooa*

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a

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Singapore

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b

Neuroscience Discovery, Janssen Research and Development, Beerse, Belgium

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Institute for Infocomm Research, Agency for Science, Technology & Research, Singapore

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9 # These authors contributed equally to this work.

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* Correspondence should be addressed to:

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Prof Kishore K. Bhakoo

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Singapore Bioimaging Consortium (SBIC)

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11 Biopolis Way, #02-02 Helios, Singapore 138667

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Tel: (65) 6478 8900; Fax: (65) 6478 9957

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Email: [email protected]

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Keywords: MR spectroscopy, stress, depression, psychosis, memantine

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Singapore Bioimaging Consortium, Agency for Science, Technology & Research,

Declarations of interest: none

ACCEPTED MANUSCRIPT Abstract

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Neuroimaging endophenotypes in animal models provide an objective and translationally-

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relevant alternative to cognitive/behavioral traits in human psychopathologies. Metabolic

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alterations, such as those involved in the glutamate-cycle, have been proposed to play a

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preponderant role in both depression and schizophrenia. Chronic Mild Unpredictable Stress

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(CMUS) and sub-chronic administration of NMDA receptor antagonist generate animal

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models of depression and schizophrenia, respectively. The models are based on

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etiologically-relevant factors related to the induction and support of these psychopathologies.

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To test metabolic alterations within the glutamate-cycle and in other major neurochemicals,

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single-voxel Magnetic Resonance Spectroscopy was recorded within the hippocampus in

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both rat models and control animals. Surprisingly, altered glutamate-related metabolites

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were observed in the CMUS model, but not NMDA-based model, as indicated by decreased

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glutamine and increased GABA levels. However, both models presented elevated total

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visible choline and inositol levels relative to controls. These results indicate the presence cell

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membrane metabolic alterations and inflammatory processes shared in both models,

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comparable to evidence presented in schizophrenia and depression and other comparable

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animal models. These translationally-relevant biomarkers may thus form the basis for drug-

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development targets in both psychopathologies.

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ACCEPTED MANUSCRIPT Table of abbreviations Chronic Mild Unpredictable Stress

Cho

Choline

CRLB

Cramer-Rao Lower Bound

Ins

Inositol

LH

Linear Hypothesis

LR

Likelihood-Ratio

MDD

Major Depressive Disorder

Gln

Glutamine

Glu

Glutamate

SVS-MRS

Single Voxel - Magnetic Resonance Spectroscopy

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CMUS

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Highlights

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SVS-MRS in rodent models of psychopathologies reveals relevant metabolic phenotype. Glutamine was increased, with a decrease in GABA level in CMUS model. Elevated Inositol and Choline concentrations in both CMUS and NMDA models.

ACCEPTED MANUSCRIPT Introduction

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Early stage drug discovery research involves animal models with an objective to mimic human

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dysfunctions through construct, predictive, etiologic and face validity. In particular, early stage

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research on psychiatric disorders, such as psychosis and depression, has primarily focused on

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characterization of effects related to behavioral dysfunction and drug efficacy. However, when it

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comes to translation of the phenotypical changes observed in rodents to behavioral symptoms and

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dysfunctions in humans, there have been a mismatch leading to erroneous inferences (Nestler and

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Hyman 2010). This could potentially be due to the fact that even the most sophisticated rodent

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models to date can only emulate a subset of complex symptoms presented by humans, particularly in

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the psychiatric arena. Thus, the need for objective biomarkers in preclinical models and efficient

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readouts with significant translational scope are critical for successful drug discovery (Wendler and

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Wehling 2010). Single Voxel - Magnetic Resonance Spectroscopy (SVS-MRS) offers a unique non-

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invasive utility to measure various brain metabolites and to quantity their concentrations within a

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specific region of interest in the brain (Duarte et al. 2012). The metabolites revealed provide insights

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into the underlying neurochemical mechanisms of psychiatric dysfunctions in both human and animal

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models.

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The metabolites revealed by SVS-MRS are directly relevant to psychopathology. Neurochemical

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imbalances have been proposed in many models of psychiatric disorders and provide objective

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biomarkers in the drug discovery process. For instance, glutamate (Glu) dysfunctions is believed to

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play a key role in psychiatric disorders such as depression (Yüksel and Öngür 2010; Luykx et al.

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2012) and schizophrenia (Marsman et al. 2013). Recent studies have proposed an overlap in the

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functional and structural signatures associated with several psychopathologies (Goodkind et al. 2015;

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Sprooten et al. 2017; Arnone et al. 2009; De Peri et al. 2012; Dong et al. 2017). Similarly, overlapping

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metabolic signatures have been reported across disorders. The interpretation of these new findings is

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hindered further due to psychiatric comorbidities. For instance, it is estimated that depression co-

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occurs in 50% of the cases of schizophrenia (Buckley et al. 2009). Animal models provide an

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excellent tool to address the metabolic contribution of specific factors in isolation, such as chronic

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stress or sub-chronic NMDA receptor antagonist administration. Studies conducted in animals allows

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for controlled conditions not attainable in studies conducted in humans, such as absence of

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premedication and societal confounds, whlist also controlling for age, gender, and stressor exposure.

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Finally, invasive and terminal experiments allow for more detailed elucidation of mechanisms

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underlying specific identified signatures.

83 To investigate the impact of chronic stress and NMDA-mediated psychosis on metabolic profiles in

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isolation, SVS-MRS was carried out within the hippocampus of two rat models. The first model, the

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chronic mild unpredictable stress (CMUS) is considered a valid model of depression (Willner 2017;

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Willner et al. 1992). Chronic stress is a major etiological factor in the induction and support of

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depressive disorders in humans (Kendler et al. 2003; Kessler 1997). The paradigm induces

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anhedonia, among other traits, a core symptom of depressive disorder (Nestler et al. 2002) used for

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diagnosis (Diagnostic and Statistical Manual of Mental Disorders, DSM-5). The second model is

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based on exposure to sub-chronic NMDA receptor antagonism, such as by ketamine or memantine,

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to induced psychosis (Krystal et al. 1994; Moghaddam et al. 1997; Javitt and Zukin 1991). The model

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is also associated with schizophrenia spectrum cognitive symptoms, caused by repeated exposure to

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NMDA receptor antagonists. Presently, the model was based on sub-chronic memantine

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administration (Sekar et al. 2013) and is characterized by hyperlocomotion, a symptom associated

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with psychosis (Forrest et al. 2014; Javitt and Zukin 1991). The main hypothesis of this study was that

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glutamate-cycle metabolite levels would be affected within the hippocampus in both models. In a

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secondary exploratory analysis, all metabolites levels recorded were compared in experimental

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models relative to control animals. The hippocampus was selected because of its putative central role

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in several psychopathologies (Campbell and Macqueen, 2004; Heckers, 2001). Moreover evidence

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gathered in our previous studies examining the whole brain using pharmacological MRI, resting state

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MRI and diffusion kurtosis MRI exemplified the role of hippocampus as a prominent region of interest

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of NMDA antagonist, memantine action (Sekar et al., 2013); as well as a key region of interest in

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investigations characterizing CMUS – MDD model (Delgado y Palacios R et al., 2011). The results

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presented herein highlight both overlapping and non-overlapping metabolic signatures between the

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two models, consistent with human psychopathologies. These results enforce the construct validity of

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both models and establishes SVS-MRS in these models as a relevant platform to advance neuro-

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psychopharmacology drug discovery research.

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ACCEPTED MANUSCRIPT 110 Methods & Materials:

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All procedures were conducted in compliance with IACUC guidelines. The study protocols were

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approved by BRC-IACUC review committee in accordance with local AVA guidelines. Male Wistar rats

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were obtained from InVivos (Singapore). Mean body weight at experimental day was 287 ± 57 gram.

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A total of 46 rats underwent SVS-MRS and an additional 41 were used separately for locomotor

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activity test. Animals were housed in enriched individually ventilated cages in groups of 4 and

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habituated to environmental conditions for at least 5 days with food and water ad libitum (conditions:

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12:12 h light/dark cycle, temperature, 20 - 24° C and humidity 45 - 65%). Rats were used only once in

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an experiment and euthanized afterwards.

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Model: Chronic Mild Unpredictable Stress

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A group of individually housed Wistar male rats (n=12) were exposed to the CMUS paradigm for 28

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days to reproduce characteristics of anhedonia (Willner et al. 1992; Willner 2017). Control animals

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were housed in groups of 2-3 rats per cage over the duration of the experiment (n=12). Animal body

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weight was measured on a bi-weekly basis. Briefly, the paradigm consists of a series of mild to

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aversive stressors. The stressor duration would last between 30 minutes to 16 hours (unless indicated

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otherwise) with a variation of up to 5 stressors a day or at night. The list of stressors included: LED

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flashing light stimulus; sound stimulus; electrical foot shock; diet restriction; water restriction;

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overnight illumination within animal holding room; cage tilt at 45˚ angle; group housing of five per

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cage; ¾ flooding of cage floor; restraint and novel odour. These stressors were applied randomly in

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combination or independently throughout the paradigm. A four to five-day interval was maintained

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between application of each individual stressor to prevent the animal from acclimatizing to a particular

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stressor. Most stressors were applied during the dark phase, particularly those involving diet and

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water restriction: this would favor elevated stress to the animal as it is nocturnal. Light, sound and

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shock: an animal stimulator (San Diego Instruments, San Diego, CA, USA) was used that delivered

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light, electrical foot shock and sound. The LED light unit did not produce heat. Different types of

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sound were controlled by random selection and amplitude with a speaker frequency of between 4 kHz

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to 30 kHz including single frequency sound or white noise. Foot shock was delivered by a constant

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current to the grid at a maximum output of 5 milliamps. Diet/water restriction and overnight

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ACCEPTED MANUSCRIPT illumination: both stressors were applied during the dark phase as they could be prolonged for

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approximately 16 hours (diet/water restriction) to about 2 days (48-hour constant illumination). Cage

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tilt with group housing and flooding: Animals were housed in static cages in groups of three and cage

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floor inclusive of bedding flooded to 1/4 height of cage. Restraint: Clear, polyfilm, cone shaped

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restraint bags (Harvard Apparatus, Holliston, MA, United States) with a small piped end opening to

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facilitate breathing is used in the restraint procedure. Significant porphyrin staining was observed on

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and around the animal’s eyes and nose during this procedure as a key indicator of stress. The

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maximum time duration for this stressor is 1½ hours. Novel odor: Pure peppermint oil was used as a

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non-predatory odor to elevate stress. Cotton balls with 4-5 drops of oil were placed in the animal’s

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cage for up to 8 hours.

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150 Model: NMDA-induced psychosis

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Memantine was obtained from Sigma-Aldrich (Singapore, Singapore). Based on the inference from

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these acute dose-response experiments previously reported (Sekar et al. 2013), subjects received

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memantine (20 mg/kg/day, IP) once daily for five consecutive days (n=15). Vehicle was administered

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in the control group (n=7). All compound solutions were stored at room temperature in a closed

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container protected from light and injection volume was 10 ml/kg.

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Sucrose preference test

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The sucrose preference test was used as an indicator of anhedonia, also known as the lack of interest

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in reward. Prior to the start of the CMUS paradigm, the animals were weighed and housed

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individually. The test was performed at day 0, day 14 and day 28 of CMUS. Each animal was

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presented with a bottle of plain water and 1% sucrose solution in the cage nozzle at the start of the

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dark cycle (7 PM). To prevent bias, the sucrose solution and water bottles were swapped between the

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two cage nozzles at the thirty-minute mark. The total duration of this test was an hour. The

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percentage of sucrose preference was calculated as: (volume of sucrose intake ÷ (volume of sucrose

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intake + water intake)) x100%.

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Locomotor activity

ACCEPTED MANUSCRIPT Locomotor activity was measured by placing rats in black perspex cylinders of Ø 30 cm and 35 cm

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height with infrared light provided via the open circular area at the bottom. Live images captured by a

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CCD-video camera (5 frames/sec) mounted 50 cm above each cylinder (12 in total) enabled image

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analysis software (Ethovision XT, Noldus, The Netherlands) to quantify total distance travelled.

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Tracking areas for each cylinder were individually calibrated and the XY coordinates of the center of

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gravity of each subject as determined to calculate total distance travelled. All experiments were

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performed during the light cycle, between 8 AM and 5 PM. Two to three days after the last sub-

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chronic administration, a subset of rats underwent the locomotor activity test. Saline was used as the

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vehicle to dissolve memantine. Animals were placed in the arenas for a 30 min habituation phase,

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followed by 60 min after administration of an acute challenge with memantine (20 mg/kg, IP) or

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vehicle. Total distance travelled was cumulated over the habituation and challenge periods

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respectively. Locomotor activity was assessed in a separate cohort of rats to avoid acute challenge

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exposure in the imaged rat groups. Groups were as follows: sub-chronic vehicle injections followed by

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memantime challenge (n=14), sub-chronic memantine injections followed by vehicle challenge (n=13),

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and sub-chronic memantine injections followed by memantine challenge (n=14).

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184 SVS-MRS data acquisition

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Initial anaesthesia was induced with 5% isoflurane in 1:2 oxygen to air mixture. Animals were

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positioned on a MR-compatible cradle, and isoflurane reduced to 2%. The animals were subsequently

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maintained with 1.5 to 2% isoflurane during the experiment. A high field 9.4T MRI (Bruker Biospin

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GmbH, Ettlingen, Germany) scanner was employed for data acquisition using a 72 mm volume coil for

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excitation and a 2x2 phased-array rat head coil for reception. SVS-MRS was acquired with a PRESS

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sequence using the following parameters: repetition time 4000 ms, echo time 13 ms, number of

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averages 128, voxel dimension 2.5 x 4 x 4 mm positioned on the hippocampus centered on ML 2.4,

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APbregma -4.2, DV 3.2 mm; acquisition time 8.40 mins/spectrum. Water suppression was carried using

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VAPOR. Four consecutive acquisitions were recorded per individual. In order to correct for eddy

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current compensation and scaling, a water unsuppressed spectrum was documented for every

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animal. Significant efforts were made during voxel positioning and shimming to achieve a consistent

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effective FWHM line-width of 8.4 to 11.8 Hz in every animal/spectrum acquired.

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ACCEPTED MANUSCRIPT Data analysis and statistics

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Metabolites were quantified using LCmodel (Provencher 1993). Statistical analysis was performed

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using R 3.2.5 (“Very, Very Secure Dishes”, The R Foundation for Statistical Computing, Vienna,

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Austria) together with lme4 (version 1.1-11) and multcomp (version 1.4-1) packages for linear mixed

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model and contrast analysis respectively. Control groups for the CMUS and NMDA paradigms were

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combined in the analysis to enhance statistical power. Experimental group effects, referring to the

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differential effect between each experimental group and the control group, i.e. CMUS vs. control and

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NMDA-induced psychosis vs. control, were tested using a linear mixed model with linear hypothesis

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(LH) tests using specifically designed contrasts. Metabolite concentration relative to total creatine was

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modelled as a function of experimental group as a fixed effect and individual animal intercepts as a

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random effect. The latter was implemented to account for multiple spectrum acquisitions per subject.

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Cramer-Rao lower bound (CRLB) estimates were used as weighting factors in the least-square fitting

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process to minimize the impacts of measurements with high estimation errors. Likelihood-ratio (LR)

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tests were used to assess interaction effects. The assumption of normality of the residuals was tested

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with QQ-plots to inspect normal distribution, Tukey–Anscombe plots for the homogeneity of the

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variance and skewness, and scale location plots for homoscedasticity. Normality of residual was

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considered plausible in all cases. The differential effect between the experimental conditions was

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tested using contrasts analysis. Statistics were corrected for false discovery rate with significance set

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at p≤0.05. Descriptive statistics are given as mean ± 1 standard deviation.

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Results

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CMUS validation: Sucrose preference test

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The CMUS procedure did not lead to weight changes or in sucrose preference compared to control

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animals (Figure 1A, LR test, CMUS effect: χ2 = 0.02, p = 0.89, Age effect: χ2 = 48.82, p = 2.8e-12).

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The decrease in sucrose preference in CMUS animals at day 28, compared to baseline, was not

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statistically significant (paired t-test, t=2.15, p=0.054). All animals presented uniform (74.5% ± 5.7)

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sucrose preference at the onset of the study. Individual animal trajectories reveal that 7/12 animals

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had a declining sucrose preference by day 28, ranging between 0 and 53%, indicative of anhedonia.

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The remaining 5/12 animals retained high sucrose preference at the end of the CMUS paradigm, 2 of

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which had aberrant sucrose preference at day 14 (Figure 1B). The latter 2 animals were not excluded

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from this study as this was not a specified a priori exclusion criterion.

231 232 NMDA-induced psychosis validation: Locomotor Activity

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Animals receiving sub-chronic memantine were 6% heavier than controls (Figure 1A, 332 ± 18 g and

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313 ± 15 g respectively, t-test, t=2.51, p=0.024). To validate the sub-chronic memantine

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administration model, locomotor activity was assessed in a separate group of rats undergoing SVS-

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MRS. This was done to prevent additional acute memantine exposure. During the initial habituation

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phase prior to the acute drug administration, there was no locomotor differences in distance traveled

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among treatment groups during the initial habituation phase, including between animals treated

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before with sub-chronic memantine compared to controls (Figure 1C, LH test, t=0.038, p=0.97).

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Locomotor activity was increased in animals receiving memantine challenge compared to those

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receiving vehicle, irrespective if the animals were in the memantine sub-chronic group (LH test,

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t=8.44, p=2e-16), or in the vehicle sub-chronic group (LH test, t=5.15, p=2.6e-7). Of special interest to

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this study, memantine sub-chronic administration further enhanced the subsequent memantine

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challenge effect on locomotion when compared to animals that had received vehicle sub-chronic

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administration (LH test, t=3.36, p=0.0008). The latter indicates a sensitization to memantine, leading

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to enhanced hyperlocomotion upon acute administration.

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Metabolic profiles are associated with CMUS and NMDA paradigms

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All MRS measurements acquired were included in the analysis. All animals recovered fully from the

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spectroscopy acquisition. None of the spectra analyzed presented any marked artefacts. Residuals

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from the metabolite quantifications were evenly distributed, indicating optimal quantifications. The

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quality of the metabolite concentration estimation was indicated by the CRLB values. The analysis

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was restricted to metabolites presenting CRLB values below 10 (Fig 2B). The majority of the

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metabolites examined in this study indicated CRLB in the range of 3 to 4, metabolites such as Glu

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were estimated with low errors (CRLB = 3.12±0.46), while GABA presented higher estimation errors

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(CRLB = 9.92±2.53). Alanine (CRLB = 35.46±12.12), Aspartate (CRLB = 14.22±3.64), Glucose

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(CRLB = 30.74±125.07), Lactate (CRLB = 675.21±437.83), N-acetylaspartylglutamate (CRLB =

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ACCEPTED MANUSCRIPT 77.63±211.10), Scyllo-inositol (CRLB = 973.51±122.55), lipids, and macromolecules we not analyzed

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due to unreliable detection. There were no group differences in total absolute creatine (LH test, tCMUS

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= 1.30, pCMUS = 0.19, tNMDA = 1.01, pNMDA = 0.31), hence metabolite levels were represented relative to

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total creatine to minimize acquisition-related variability. Likewise, there were no differences in

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metabolite level between the two control groups (NMDAcontrol n=12, CMUScontrol n=7, LH test, t-value

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range = [-1.56, 1.08], minimum p-value = 0.12). To strengthen statistical power, both control groups

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were merged for the remainder of the analysis.

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The CMUS paradigm lead to a significant effect on neurotransmitter-related metabolites; a decrease

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in glutamine (Gln) (LH test, tCMUS = 2.42, pCMUS = 0.015) and an increase in GABA (LH test, tCMUS = -

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2.49, pCMUS = 0.012) with respect to the control group, while there were no differences in the NMDA-

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induced psychosis group (Figure 3). Both experimental procedures also converged toward

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comparable metabolite profile; inositol (Ins) was increased in both groups relative to controls (LH test,

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tCMUS = -3.39, pCMUS = 6.89x10 , tNMDA = -4.68, pNMDA = 2.78x10 ). In addition, both total visible choline

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(glycerophosphocholine + phosphocholine, Cho) and taurine concentrations presented a significant

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effect of CMUS effect, and a comparable trend in the NMDA group. Total Cho was increased in both

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groups, although the effect did not survive false discovery rate correction in the NMDA vs. control

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comparison (LH test, tCMUS = -2.69, pCMUS = 0.007, tNMDA = -2.28, pNMDA = 0.022). Taurine was reduced

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following the CMUS paradigm compared to control (LH test, tCMUS = 2.35, pCMUS = 0.018), while only a

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trend was observed in the NMDA group (LH test, tNMDA = 1.71, pNMDA = 0.087). In the above analysis,

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all individuals undergoing CMUS paradigms were included. A correlation analysis was carried out to

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test for an association between sucrose preference and metabolite profiles in the hippocampus

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(Figure 4). An association between NAA and sucrose preference (r = 0.66, puncorrected = 0.017) did not

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survive multiple comparison corrections. Beyond this, no significant associations could be established

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between metabolites and sucrose preference.

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Discussion

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Neuroimaging-based biomarkers have the potential to reveal mechanisms underlying pathologies and

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for an endophenotypic-based demarcation of psychiatric illnesses. Moreover, they allow for objective

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metrics in the drug discovery process. To elucidate the specific contribution of relevant factors to the

ACCEPTED MANUSCRIPT induction and support of psychopathologies on the metabolic profiles within the hippocampus, two rat

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models underwent SVS-MRS assessment. We observed both distinct and shared metabolic

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signatures between the two animal models. Interestingly shared signatures, such as structural and

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metabolic are increasingly reported across psychiatric disorders (Goodkind et al. 2015; Sprooten et al.

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2017; Arnone et al. 2009; De Peri et al. 2012; Dong et al. 2017), including in depressive disorders and

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schizophrenia. Part of the issue may be explained by the co-occurrence of brain disorders. For

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instance, depressive disorders are known to be comorbid with schizophrenia (Buckley et al. 2009);

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however this association may be more complex, as chronic stress may trigger psychosis (Corcoran et

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al., 2002; van Winkel et al., 2008). Considering these results beyond traditional nosological

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delineations, such as through the lens of the Research Domain Criteria (Cuthbert, 2015), it may hold

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the key to advancing our understanding of psychopathologies and open new treatment avenues.

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Glutamate-related hypotheses have been considered in both depressive disorders (Sanacora et al.

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2012) and psychosis (Goff and Coyle 2001). Both Glu and its decarboxylated derivative GABA are the

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most abundant neurotransmitters in the brain, and represent, together with Gln, key metabolites in

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multiple pathways such as synaptic transmission, energy metabolism, and protein synthesis. In a

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2010 review, Glx, the combined concentration of Glu and Gln, was reported to be reduced in major

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depressive disorders (MDD) spanning across different regions, including the hippocampus (Yüksel

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and Öngür 2010). Moreover, in 3 out of 4 studies that reported on Glu and Gln separately, Gln

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concentrations were found reduced but not Glu. Reduced Glx associated with MDD was also reported

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in separate meta-analyses (Luykx et al. 2012; Yildiz-Yesiloglu and Ankerst 2006) however Glx effects

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were not observed at high field (Evans et al., 2018). These observations are corroborated in animal

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models of chronic stress, an etiological factor for depression. Reduced Glu were reported in the

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hippocampus in rats following chronic mild unpredictable stress (Hemanth Kumar et al. 2012), chronic

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forced swim stress (Li et al. 2008), in rats bred for learned helplessness (Schulz et al. 2013), in dams

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following an interaction between an acute exposure to forced swim stressor in their adolescence and

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gestational chronic mild unpredictable stress (Huang et al. 2016), and prefrontal cortex of mice in the

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social defeat stress model (Veeraiah et al. 2014). These were accompanied with reduction in Gln (Li

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et al. 2008, Hemanth Kumar et al. 2012, Veeraiah et al. 2014), highlighting the complex interplay

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between Glu and Gln in relation to chronic stress.

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ACCEPTED MANUSCRIPT 319 In addition to Glx, GABA is also affected in MDD, although it is generally considered to be reduced in

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cortical areas (Sanacora et al. 2002), in plasma (Petty and Schlesser 1981; Petty and Sherman 1984)

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and in CSF (Gerner and Hare 1981). In animal models, the patterns of GABA alteration appear less

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clear. GABA was increased in the hippocampus of offspring exposed to the chronic mild unpredictable

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stress upon a challenge by an acute stressor (Huang et al. 2016), elevated in ex-vivo prefrontal cortex

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following chronic mild stress (Perrine et al. 2014) and cingulate cortex following restraint stress

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(Drouet et al. 2015). Yet, GABA was reduced in the prefontal cortex of both postnatal stress (Gapp et

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al. 2017) and social defeat model (Veeraiah et al. 2014), together with reduced glutamate-

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decarboxylase gene expression levels, the enzyme responsible for Glu to GABA conversion

329

(Veeraiah et al. 2014). These conflicting results remain difficult to interpret as different animal models

330

and regions were involved. The results reported here indicate elevated levels of GABA, suggesting

331

altered inhibitory neurotransmission in the hippocampus. Taken together with elevated Gln levels, the

332

metabolic levels estimated in CMUS relative to control animals point toward a generalized

333

dysregulation of the glutamate-glutamine cycle dysregulation associated with chronic stress (Abdallah

334

et al., 2018).

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Interestingly, we observed Gln and GABA effects only in the CMUS model, but not in the NMDA-

337

induced psychosis model. This was unexpected as the latter model relies specifically on Glu

338

disruption through sub-chronic NMDA receptor antagonism to induce a psychosis-like condition. To

339

date, only few results have been reported in relation to NMDA-induced psychosis, either in human or

340

animal models compared to schizophrenia or MDD. A meta-analysis revealed there was an overall

341

decrease in Glu and increase in Gln in patients with schizophrenia or first-event psychosis compared

342

to healthy controls (Marsman et al. 2013). Acute ketamine administration lead to increased Gln

343

(Rowland et al. 2005), increased Glu (Stone et al. 2012, Evans et al., 2018), or no effect on either

344

metabolites in humans (Taylor et al. 2012). In animal models, reduced Glu and increased Gln levels

345

were reported following acute phencyclidine administration, another NMDA-agonist, in rat prefrontal

346

cortex (Iltis et al. 2009), similar to patients with schizophrenia (Marsman et al. 2013). Yet, an opposite

347

finding was reported following 6 days sub-chronic ketamine administration in rats (Kim et al. 2011).

348

This may be consistent with new insight on the acute and sub-chronic effects of ketamine as rapid

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ACCEPTED MANUSCRIPT 349

acting anti-depressant (Abdallah et al., 2018, Evans et al., 2018); although, the effects in the context

350

of NMDA-induced psychosis remain unclear.

351 Other metabolites identified in this study have also been implicated in both MDD and psychosis. For

353

instance, elevated Cho was found in MDD (Yildiz-Yesiloglu and Ankerst 2006) and in groups at high

354

risk to psychosis (Wood et al. 2003). Interestingly, in our study both the CMUS and NMDA cohort

355

showed a significant increase in this metabolite within the hippocampus. It is essential to note that

356

phosphatidylcholine (PC), the main choline compound which contributes to the total Cho levels is

357

invisible

358

glycerophosphocholine (GPC) are linked to the synthesis & degradation of phosphatidylcholine, which

359

is incorporated in the cell and its myelin membranes. In animal models, increased Cho was found in

360

the hippocampus following an acute but not prolonged restraint stressor (Han et al. 2015), and in the

361

prefrontral cortex following chronic social defeat in mice (Grandjean et al. 2016). In the latter model,

362

the same group reported decreased expression of oligodendrocyte-myelination genes (Azzinnari et al.

363

2014; Cathomas et al. 2018), thus providing potential supporting mechanisms for phospholipid

364

metabolism and/or cell membrane catabolism alterations in the models investigated presently. In

365

addition to Cho, a significant increase in the Ins levels was also observed in both cohorts. Similar

366

observations were observed in the prefrontal cortex of depressed patients (Venkatraman et al. 2009;

367

Caetano et al. 2005) and in the striatum of first-psychosis episode groups (Plitman et al. 2016),

368

substantiated with increased blood cytokine levels in both patient groups with depression and

369

schizophrenia (Goldsmith et al. 2016). Kim et al. (2010), Hemanth Kumar et al. (2012) and Grandjean

370

et al. (2016) have reported a similar increase in Ins levels in either hippocampus or amygdala

371

following acute forced swim test, CMUS, and chronic social defeat model respectively. Levels were

372

however decreased in the prefrontal cortex in a murine model of social isolation (Corcoba et al. 2017).

373

Ins, an intracellular lipid precursor of phosphatidylinositol structural lipids (Berridge and Irvine 1989;

374

Berridge 2009) is predominantly expressed in myelin lipid membranes and glia (Duarte et al. 2012). It

375

is generally interpreted to reflect the nature of proliferation and/or glial cell function. In other words,

376

fluctuations in the levels of Ins is conceived to be a proxy of potential inflammation and cell membrane

377

metabolism. Interestingly, gene expression of genes associated with inflammatory processes and

378

inflammatory-related metabolites were found increased in the chronic social stress model in limbic

an

MRS

investigation,

only

the

cytosolic

phosphocholine

(PCh)

and

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ACCEPTED MANUSCRIPT regions including the hippocampus (Azzinnari et al. 2014; Fuertig et al. 2016), providing a putative

380

supporting mechanism to the underlying increased Ins levels induced by chronic stress. Finally, Tau

381

levels were found to be deceased in the CMUS model, and a trend was observed in the NMDA group.

382

Tau is increasingly considered a neuroprotectant, which may regulate calcium levels and protect

383

against Glu excitotoxicity (Wu and Prentice, 2010). Together, the results obtained are consistent with

384

inflammatory-related and cell membrane turnover processes being shared in both models. Confirming

385

the link between gene expression, specific cellular events, and Cho and Ins levels may strengthen the

386

translation relevance of these findings and highlight targets for drug discovery. It emerges from the

387

results presented here, and elsewhere, that these metabolites could be robust and translatable

388

biomarkers to assess therapeutic engagements in both human and animal models, especially in the

389

context of neural inflammation and circuit re-modelling.

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In view of the above, a number of limitations need to be considered. First, imaging was carried out in

392

male rats only to have maximally homogenous groups. However, gender interaction effects with either

393

conditions are likely to occur. This is specifically relevant given gender distribution disparities in mood

394

and affective disorders (Piccinelli and Wilkinson, 2000). Second, SVS-MRS studies were limited to the

395

observation within one or few predefined volumes of interest. These vary greatly from study to study

396

and it remains unclear if results from one area can be compared to another. Imaging time constraint

397

often prevents the investigation of multiple locations within the same subjects. Spectroscopic imaging

398

(Posse et al. 2013) would thus offer a broader overview of metabolite profiles across several brain

399

regions and has been applied in the rodent brain (Seuwen et al. 2015). This sensitive methodological

400

improvement removes reporting bias toward predefined volumes of interests in SVS-MRS studies.

401

Beyond spatial localization, enhanced 2D spectroscopy, such as J-resolved methods (Huang et al.,

402

2015), are likely to improve metabolite estimation confidence; however, its application in vivo has so

403

far remained limited. Moreover, in light of the variability of the results between animal models and

404

human studies, it appears that further validation is warranted either through independent

405

measurements, e.g. with micro-dialysis, or through multi-center studies and meta-analysis. The third

406

limitation is regarding the number of behavioral dimensions used to test the models. Presently, each

407

model was tested along one dimension, anhedonia in the CMUS model and hyperlocomotion in the

408

NMDA exposure model. The CMUS paradigm applied here did not lead to equally robust anhedonia

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ACCEPTED MANUSCRIPT in all animals equally; however, it was not possible to relate variation in sucrose preference to specific

410

metabolic concentration changes. Hyperlocomotion is a proposed measure in animal models of

411

psychosis (Forrest et al. 2014; Javitt and Zukin 1991). However, hyperlocomotion was tested in a

412

separate model group of animals to avoid additional memantine exposure in the experimental group,

413

precluding comparisons at the individual level. Behavioral dimensions were not assessed across both

414

models. It is thus not possible to infer from this study on the hedonic state in the sub-chronic

415

memantine model or the locomotor activity in the CMUS animal. These observations may of interest

416

in providing new approaches to classify psychiatric disorders (Cuthbert, 2015). Unfortunately, these

417

concerns were not considered in the study design. Hence, a broader examination across behavioral

418

dimensions in these models may reveal correlates of the metabolic fingerprints established here and

419

elsewhere. Additional behavioral dimensions may also provide further confidence in estimating

420

‘resilience’ status in animals, a first step toward highlighting the metabolic correlations of behavioral

421

states. This latter endeavor would however necessitate an adapted study design, including sufficient

422

group size to investigate sub-groups within a condition. Finally, SVS-MRS was acquired in

423

anesthetized animals to prevent animal distress and to reduce motion. In a previous study, prolonged

424

isoflurane was found to elevate lactate levels compared to Propofol (Makaryus et al., 2011). Similar

425

effects may not be excluded in the present study.

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In summary, the aim of this study was to compare the metabolic signature within the hippocampus in

428

rat models of chronic stress and psychosis. Metabolites within the glutamate-cycle, Gln and GABA,

429

were found affected in the CMUS model relative to control but not in the NMDA antagonist condition,

430

while both models presented elevated Ins and total visible Cho levels. Interestingly, these results

431

relate to observations made in other rodent models, and more so, to studies conducted in humans.

432

Comparable metabolic profiles enhance the face validity of these models and make them jointly with

433

SVS-MRS an attractive platform in the drug discovery process and in the investigations of the

434

underlying mechanisms behind these biomarkers of psychopathology.

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Declaration of Interest

437

The authors have no conflict of interest to declare.

438

ACCEPTED MANUSCRIPT Acknowledgements

440

We acknowledge the generous funding support from the Joint Council Office – Agency of Science,

441

Technology & Research (JCO-A*STAR) through the Platform Development (DP) Grant. We would

442

also like to sincerely acknowledge the seamless guidance extended by Dr. Carrie Jones and her

443

team, from Vanderbilt Centre for Neuroscience Drug Discovery, Vanderbilt University, US towards

444

setting-up chronic mild unpredictable stress animal model in our facility in SBIC, A*Star, Singapore.

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445 446

Figure legends

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447 448

Figure 1 | A) Animal weight in CMUS and NMDA groups and their respective controls. An age effect

450

between baseline (day 0) and post-treatment (day 28) weight was observed in the CMUS and control

451

condition (χ2 = 48.82, p = 2.8e-12). Memantine sub-chronic administration was associated with

452

greater weight in the NMDA group relative to control (t-test, t=2.51, p=0.024). B) Sucrose preference

453

in CMUS rats over the course of the paradigm. Black line indicates group mean, coloured lines

454

indicate individual animal trajectories. 7/12 animals present a decline in sucrose preference over the

455

course of the paradigm. C) Locomotor activity in rats following memantine challenge in rats that

456

underwent sub-chronic memantine treatment (‘sub-treat’). Relative to habituation (light grey), post-

457

challenge (dark grey) locomotion was increased in animals that received memantine (MEM) in the

458

challenge compared to vehicle (VEH). Animals that underwent sub-chronic memantine administration

459

walked more distance in the post-challenge session relative to habituation compared to rats receiving

460

sub-chronic vehicle injections (LH test, t=3.36, p=0.0008). The latter observation denotes a

461

sensitization effect to a memantine challenge associated with memantine sub-chronic administration.

462

Data is represented as mean ± 1 SD.

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Figure 2 | A) Single voxel positioned on the hippocampus in a representative animal, shown as an

465

overlay on axial, coronal, and sagittal anatomical sections. B) Cramér–Rao lower bound values

466

indicating the precision of the metabolite concentration estimation. Only metabolites with Cramér–Rao

467

lower bound below 10 were considered in our analysis. Data is represented as mean ± 1 SD.

468

ACCEPTED MANUSCRIPT Figure 3 | Metabolite concentration estimated from SVS in the hippocampus. The CMUS paradigm is

470

associated with a decrease in glutamine and an increase GABA concentration relative to the control

471

group. Inositol and total choline were elevated in both experimental groups relative to control, while

472

taurine showed a trend toward decrease. All concentrations are indicated relative to total creatine.

473

Points represent individual animals, red lines indicate group mean, labels indicate: # p≤0.05

474

(uncorrected), * p≤0.05 (corrected), ** p≤0.01 (corrected), *** p≤0.001 (corrected).

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Figure 4 | Metabolite concentration as a function of sucrose preference in CMUS rats. There was no

477

significant association between sucrose preference in CMUS animals and metabolite concentrations

478

recorded from SVS in the hippocampus. Triangles and circles represent resilient and susceptible

479

individuals respectively. Red lines represent least-square regression line.

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