Little evidence for neurometabolite alterations in obsessive-compulsive disorder - A systematic review of magnetic resonance spectroscopy studies at 3 Tesla

Journal Pre-proof Little evidence for neurometabolite alterations in obsessive-compulsive disorder - A systematic review of magnetic resonance spectroscopy studies at 3 Tesla Eline L. Vester, Niels T. de Joode, Chris Vriend, Petra J.W. Pouwels, Odile A. van den Heuvel PII:

S2211-3649(19)30116-2

DOI:

https://doi.org/10.1016/j.jocrd.2020.100523

Reference:

JOCRD 100523

To appear in:

Journal of Obsessive-Compulsive and Related Disorders

Received Date: 17 July 2019 Revised Date:

5 November 2019

Accepted Date: 11 February 2020

Please cite this article as: Vester E.L., de Joode N.T., Vriend C., Pouwels P.J.W. & van den Heuvel O.A., Little evidence for neurometabolite alterations in obsessive-compulsive disorder - A systematic review of magnetic resonance spectroscopy studies at 3 Tesla, Journal of Obsessive-Compulsive and Related Disorders (2020), doi: https://doi.org/10.1016/j.jocrd.2020.100523. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. 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. © 2020 Published by Elsevier Inc.

Little

evidence

for

neurometabolite

alterations

in

obsessive-

compulsive disorder - a systematic review of magnetic resonance spectroscopy studies at 3 Tesla

Eline L. Vestera,*, Niels T. de Joodea,*,†, Chris Vrienda,b, Petra J.W. Pouwelsc, & Odile A. van den Heuvela,b a

Amsterdam UMC, Vrije Universiteit Amsterdam, department of Anatomy & Neurosciences, Amsterdam Neuroscience, de

Boelelaan 1117, Amsterdam, Netherlands. b

Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Psychiatry, Amsterdam Neuroscience, de Boelelaan 1117,

Amsterdam, Netherlands. c

Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Radiology and Nuclear Medicine, Amsterdam

Neuroscience, de Boelelaan 1117, Amsterdam, The Netherlands * These two authors contributed equally †

Corresponding author. Department of Anatomy and Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, P.O.

Box 7057, 1007 MB Amsterdam, Netherlands. E-mail address: [email protected]

Abstract Obsessive-compulsive disorder (OCD) is a neuropsychiatric disorder that can affect individuals across the entire lifespan. Dysregulations of the cortico-striato-thalamo-cortical (CSTC) circuits may contribute to the pathophysiology of this disorder. Previous studies have used proton magnetic resonance spectroscopy (1H-MRS) to detect neurometabolic abnormalities in the CSTC circuits of OCD patients. In this study, we systematically reviewed studies that used 3 Tesla 1H-MRS to investigate neurometabolite concentrations in OCD patients versus healthy controls. We also reviewed associations between neurometabolite concentrations and symptom severity and the effect of treatment. Out of the 1161 articles that were identified by our literature search, 22 articles met our inclusion criteria for this review. Most studies did not demonstrate any neurometabolite abnormalities in OCD patients compared with controls, but some mixed results were found depending on the region of interest. The most consistent findings showed lower gamma aminobutyric acid (GABA) concentrations in the rostral anterior cingulate cortex (rACC) and higher choline concentrations in the thalamus of adult OCD patients compared to controls. Glutamate concentrations decreased after treatment in one study, but not in another. Some studies reported a correlation between neurometabolite concentrations and symptom severity, but the direction of this relation remains unclear and might be dependent on the brain region. These results do not provide strong evidence for OCD-related neurometabolite abnormalities. Because of the inconsistent results and the large heterogeneity between studies, more research is needed to investigate the exact role of neurochemistry in OCD and the utility of 1H-MRS to study it.

Keywords: Obsessive-compulsive disorder, magnetic resonance spectroscopy, neurometabolite alterations, treatment effects, symptom severity.

1. Introduction Obsessive-compulsive disorder (OCD) is a prevalent neuropsychiatric disorder manifesting with obsessions and compulsions, affecting 1-3% of the general population (Ruscio et al., 2010). Obsessions are marked as persistent, intrusive and distressing thoughts, which are often accompanied by repetitive behavioural or mental acts, also known as compulsions (Bokor et al., 2014; Stein et al., 2019). The cortico-striato-thalamo-cortical (CSTC) circuits have often been found to be involved in the pathogenesis of OCD by showing structural (Boedhoe et al., 2017; Pujol et al., 2004), functional (Harrison et al., 2009) and neurometabolic abnormalities (Naaijen et al., 2015) as well as abnormal activity during cognitive tasks, including error-processing (Fitzgerald et al., 2005), memory (van der Wee et al., 2003) and planning (van den Heuvel et al., 2005). Abnormal brain activation has also been demonstrated in OCD during emotional processing (Thorsen et al., 2018). The CSTC circuits are mainly glutamatergic on the cortical-striatal and thalamic-cortical level but a complex interplay of excitatory and gamma aminobutyric acid (GABA) inhibiting projections can be found on the subcortical level (Pittenger et al., 2011; Stein et al., 2019; Tekin et al., 2002). Increasing evidence demonstrates dysregulations of glutamate (Glu) and GABA in the CSTC circuits in OCD and genes coding for the glutamate signaling cascade, including GRID2, GRIK2 and SLC1A1, are associated with OCD (International Obsessive Compulsive Disorder Foundation Genetics et al., 2018; Pittenger et al., 2011; Stein et al., 2019; Wu et al., 2012). Neurometabolite concentrations can be quantified in vivo using proton magnetic resonance spectroscopy (1H-MRS), a non-invasive magnetic resonance imaging technique. 1H-MRS allows for the quantification of important regulators of neuronal activity such as glutamine (Gln), Glu and GABA (Govindaraju et al., 2000). Given the high similarity of molecular structures, Glu and Gln are often difficult to measure separately in 1H-MRS studies at low field strength and are therefore frequently pooled together and referred to as Glx (Zhang et al., 2016a). Other neurometabolites that can be measured using 1H-MRS, include choline-containing compounds (Cho), creatine + phosphocreatine (tCr), N-acetylaspartate (NAA) and myo-inositol (Ins) (Brennan et al., 2013; Michaelis et al., 1991).

Cho is a marker for cell membrane metabolism (Govindaraju et al., 2000). Cr is a high-energy compound and is thought to remain stable with age, it is therefore often used as a reference marker (Govindaraju et al., 2000). NAA synthetization takes place in neuronal mitochondria and is considered to reflect neuronal integrity (Aoki et al., 2012). Although the function of Ins is not well understood, it is used as a marker of glial cells (Chang et al., 1999; Govindaraju et al., 2000). Previous 1H-MRS studies have demonstrated alterations in neurometabolite concentrations in both pediatric and adult patients with OCD (Brennan et al., 2013; Naaijen et al., 2015). In one of the earliest studies, Rosenberg et al. (2000) demonstrated higher Glx concentrations in the caudate nucleus of OCD patients at baseline and a decrease in Glx after treatment that correlated with symptom improvement. This led to the hypothesis of glutamate dysregulation as an important contributor to the pathophysiology of OCD. Since then, more studies have shown Glx abnormalities (Naaijen et al., 2015; Pittenger et al., 2011), but also changes in NAA, Cho and Cr concentrations have been reported (Mirza et al., 2006; Rosenberg et al., 2001). Abnormal NAA concentrations seem to be normalized by cognitive behavioural therapy (CBT) in both pediatric and adult OCD patients (Atmaca et al., 2015; O'Neill et al., 2012), and psychotropic medication has been shown to increase NAA concentrations in adult patients (Jang et al., 2006). Nevertheless, there are considerable inconsistencies in the reported alterations (Starck et al., 2008; Whiteside et al., 2012). These inconsistencies may possibly be related to differences in methodology; for example the use of low magnetic field strength of 1.5 Tesla in earlier studies, whereas more recent studies are often scanned at higher field strengths of 3 Tesla (3T). A major advantage of 3T 1H-MRS is the higher signal-to-noise ratio which allows better separation of the neurometabolite peaks, including separation the spectral peaks of Glu and Gln (Ohkubo et al., 2002). This review aims to summarize and identify abnormalities in neurometabolite concentrations in OCD patients using 3T 1H-MRS. Thereby providing an update on the last six years of 1H-MRS in OCD with an exclusive focus on 3T 1H-MRS. As structural and functional brain alterations of OCD have previously been shown to differ across the lifespan (Boedhoe et al., 2017; Friedlander et al., 2006), we expect differential effects of pediatric and adult OCD on neurometabolite alterations and therefore consider them separately. We also summarize

the reported associations with symptom severity and the effects of treatment (CBT and serotonergic medication).

2. Methods For this review, we searched for English articles in the databases PubMed and Web of Science (search date: 02/02/19). We used the following keywords: ‘proton magnetic resonance’ or ‘H-MRS’ or ‘MR spectroscopy’ or ‘magnetic resonance spectroscopy’ or ‘1H spectroscopy’, in combination with ‘obsessive-compulsive disorder’ or ‘OCD’. As this review only focuses on studies with a 1H-MRS magnetic field strength of 3T, the search was restricted to articles from 2000 to now. Studies were included (1) when they focused on OCD patients diagnosed according to the Diagnostic and Statistical Manual of Mental Disorders (DSM) criteria, (2) when the OCD severity was measured according to the (Child) Yale-Brown Obsessive Compulsive Scale (CY-BOCS for children or Y-BOCS for adults) (Goodman et al., 1989), (3) when the study used 1H-MRS to measure neurometabolite concentrations and (4) when the study was a case-control study in which neurometabolite concentrations were compared between OCD patients and controls. Exclusion criteria were a lower magnetic field strength than 3T, the use of pharmacological treatment other than selective serotonin reuptake inhibitors (SSRIs) or serotonin-norepinephrine reuptake inhibitors (SNRIs), the focus on neurometabolites other than glutamine (Gln), glutamate (Glu), glutamine+glutamate (Glx), gamma aminobutyric acid (GABA), N-acetylaspartylglutamate + N-acetylaspartate (tNAA), choline (Cho), myo-inositol (Ins) or creatine (Cr), case-studies and reviews. After the database search, two separate researchers (ELV, NTdJ) screened the articles for relevance based on title and discrepancies were discussed with a senior researcher (CV). Next, abstracts and full-texts were read to define the final set of studies for this systematic review. Reference lists from the included studies were hand-searched to ensure the most accurate overview. Different aspects from the selected studies were identified. Demographic and clinical characteristics were identified to determine the number of subjects and to classify subjects as pediatric (age < 18) or adult (age ≥ 18), (C)Y-BOCS score as a measure of symptom severity, comorbidities, medication status,

experimental design, 1H-MRS parameters (e.g. field strength, sequence and voxel size), voxel placement, neurometabolites and quantification method. Findings were grouped by brain region. Quality of the identified studies was assessed by two separate researchers (ELV, NTdJ) according to the NIH quality assessment questionnaire for case-control studies (https://www.nhlbi.nih.gov/healthtopics/study-quality-assessment-tools). As the volumes of interest (VOIs) varied greatly between the included studies, we were not able to conduct a meta-analysis. Our analysis plan was preregistered with PROSPERO (for protocol details see https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=128264).

3. Results Of the 1161 studies that were retrieved with our search terms, 22 studies met our inclusion and exclusion criteria and were included in this review (see flowchart in Figure 1). Twenty studies compared the neurometabolite concentrations between OCD patients and healthy subjects, whereas two studies examined the effect of CBT on neurometabolite concentrations. Of these studies, five examined pediatric patients and 17 studies included adult OCD patients. All studies had some restrictions concerning comorbid disorders, whereas only eight studies excluded all comorbid axis I psychiatric disorders. In eight studies the patients were free of medication during the time of scanning and one study included medication naïve patients. Twelve of the included studies focused on the rostral anterior cingulate cortex (rACC), six studies looked at the dorsal anterior cingulate cortex (dACC), eight studies at the striatum, six at the thalamus, three at the dorsolateral prefrontal cortex (DLPFC), two at the posterior cingulate cortex (PCC), two at the frontal white matter (WM), one at the parietal WM and one at the orbitofrontal cortex (OFC). See Table 1 for an overview of the studies and their main results.

Figure 1. Flow diagram of study selection. After screening for eligibility, a total of 22 articles were included in this systematic review.

Table 1. Overview 1H-MRS studies included for analysis References

Subjects

(C)Y-BOCS

Comorbidities

scores

Medication

Experimental

1

status

design

and parameters

H-MRS sequence

Mean ± SD

Brennan et al. (2015)

Adults 30 OCD

All ≥ 18, 27.8 ± 2.6

29 HC

Region of interest and

Neurometabolites

Voxel size (RL–AP–SI)

Schizophrenia,

Medication

Baseline

TD, ASD,

affecting

comparison

bipolar disorder

glutamatergic

OCD and HC

and substance

system

TE = 35 – 350 (22

abuse excluded

excluded,

TE’s with delta 15

other stable ≥

ms)

4 weeks

2D JPRESS TR = 2000

rACC

Quantification

Partial volume

method and

effect

Quantification

correction

Results (OCD vs. HC)

units Gln, Glu,

20x20x20mm

LCModel

Yes

No differences between OCD and HC.

tCr ratios and Gln/Glu ratio

NEX = 352 (16 per TE)

Brennan et al. (2016)

Adults 29 OCD

All ≥ 18, 27.6 ± 2.2

25 HC

Schizophrenia,

Medication

Baseline

TD, ASD,

affecting

comparison

bipolar disorder

glutamatergic

OCD and HC

and substance

system

abuse excluded

excluded,

2D JPRESS TR = 2000

PCC

Cho, GABA, Gln,

20x20x20mm

Glu, GSH, Ins, tNAA

TE = 35

LCModel

Yes

Lower GSH/Cr levels in OCD.

tCr ratio and Glu/Gln ratio

No differences in other metabolite ratios.

NEX = 352

other stable ≥ (16 per TE)

4 weeks Fan et al. (2017)

Adults

11.7 ± 4.7

20 OCD 22 HC

al. (2017)

Adults 23 OCD

1

Baseline

major

antipsychotic

comparison

neurological

medication, 5

OCD and HC

disorder

SSRIs

All ≥ 20, 29.9 ± 4.5

PRESS

dACC: 16x25x16mm

Cho, Cr, Gln, Glu, Ins, tNAA

TR = 3000

LCModel

Yes

Water scaling

ACC: no differences Thalamus: trend higher

Thalamus: 28x16x16mm

Cho in OCD (p=0.06),

TE = 35

positive correlation Glu

excluded

12 TD Hatchondo et

Psychosis and

NEX = 64

All other axis I

SSRIs and

Baseline

psychiatric

benzodiazepi

comparison

disorders

nes allowed

OCD and HC

semi-LASER MRSI TR = 1700

and anxiety scores. rACC Striatum

Cho, Cr, tNAA

JMRUI Water scaling;

Thalamus (values from left and right

Yes

rACC: higher Cho and Cho/Cr, lower tNAA/Cho in OCD.

and tCr or Cho

22 HC

excluded

TE = 135

VOIs averaged)

ratios

Striatum: higher Cho, Cho/Cr and tNAA/Cr,

NEX = 2 Voxels within MRSI VOI:

lower tNAA/Cho in

15x15x20mm

OCD. Thalamus: higher Cho, lower tNAA/Cho in OCD.

Kitamura et al. (2006)

Adults

20.4 ± 2.4

12 OCD

No comorbid

SSRIs

Baseline

psychiatric

comparison

disorders

OCD and HC

32 HC

PRESS

dACC: 15x20x10mm,

Cho, tNAA

TR = 2000 Basal ganglia: 15x30x15mm,

Software on GE

No

Cho/Cr, trend higher

under the curve

tNAA in OCD. Cho/Cr

TE = 80

positive correlated Y-

Cr ratios Thalamus and WM NEX = 96, dACC and putamen NEX =

Parietal WM: higher

scanner, areas

Thalamus, frontal WM and

BOCS.

parietal; WM: all 15x15x15mm

128 Moon & Jeong (2018)

Adults 18 OCD

All ≥ 7,

Not specified

26.7 ± 4.6

Psychotropic

Baseline

PRESS

Right DLPFC

Cho, α-Glx (3.65-

Software on

medication

comparison

TR = 2000

20x20x20mm

3.80 ppm), β-γ-Glx

Siemens

lower tNAA/Cr and

(2.05 – 2.50 ppm),

scanner, areas

Cho/Cr in OCD.

Ins, Lactate, Lipids,

under the curve

OCD and HC 18 HC

TE = 30 NEX = 96

Naaijen et al. (2017)

Children 29 OCD 53 HC 51 ASD

17.5 ± 7.1

Other disorder

Antipsychotic

Baseline

of interest

s and

comparison

(ASD) excluded

antidepressant

OCD and HC

s, medication free ≥ 48h

PRESS TR = 3000

tNAA

rACC

Glu en Glx (in

Left Striatum

supplements)

20x20x20mm TE = 30 NEX = 96

No

Higher β-γ-Glx /Cr,

Cr ratios

LCModel Water scaling

Yes

rACC: higher Glu (and Glx, in supplements) in OCD. Positive correlation rACC Glu and compulsive behaviour in OCD. No medication effects.

Naaijen et al. (2018)

Children

18.7 ± 7.3

32 OCD

Other disorder

Antipsychotic

Baseline

of interest

s and

comparison

(ASD) excluded

antidepressant

OCD and HC

56 HC

O’Neill et al.

free ≥ 48h

(2016)

Adults

All ≥ 14,

40 OCD

25.2 ± 4.3

16 HC

Psychotic and

TR = 3000

Left Striatum

Glu, tNAA

20x20x20mm

LCModel

Yes

No significant differences.

Water scaling

TE = 30

s, medication

54 ASD

PRESS

NEX = 96

SSRIs, stable

Baseline

bipolar disorder,

dose ≥ 12

comparison

substance abuse

weeks at time

OCD and HC

and ADHD

of enrolment

PRESS TR = 2000

rACC

Cho, Cr, Glu, Glx,

dACC

Ins, tNAA

LCModel

Yes

rACC: higher Glx in OCD.

Water scaling

Thalamus

dACC: Glu, Cho, Cr, Ins

TE = 30

and Glx lower in

excluded

NEX = 96

From left and right

medicated versus

hemispheres (6 VOIs)

unmedicated patients.

15x15x15mm Cho and Cr negative correlation Y-BOCS (rACC) and depressive symptoms (rACC and dACC). O’Neill et al. (2017)

Children 49 OCD

All ≥ 16, 23.9 ± 3.7

29 HC PCC

Developmental

Medication

12-14 weekly

disorder,

affecting

CBT sessions

psychotic

glutamatergic

disorder and

system

substance abuse

excluded,

excluded

other stable ≥

Pre-treatment PCC Glu

12 weeks

positively correlated to

20 OCD

PEPSI, MRSI TR = 2000 TE = 15 NEX = 8

rACC

Glu

PCC

LCModel

Yes

Baseline no significant differences.

Water scaling

rACC: decrease Glu Voxels within MRSI VOI:

after CBT in OCD.

7.6x7.6x9mm

change CY-BOCS after

12 HC

CBT. Ortiz et al. (2015)

Children 47 OCD

17.3 ± 9.4

Psychotic

78% received

Baseline

disorder, TD

SSRIs

comparison

and autism 31 HC

excluded

PRESS TR = 2000

rACC

Cho, Cr, Glx, Ins,

15x20x10mm

tNAA

LCModel Water scaling

Yes

In OCD lower Ins, Glx significantly higher when illness duration ≥

OCD and HC TE = 35

24 months versus < 24

NEX = 156

months. No medication effects.

Park et al. (2017)

Adults

All ≥ 24,

14 OCD

27.3 ± 4.4

14 HC

Simpson et al. (2012)

Adults 24 OCD

Neurological or

Antipsychotic

Baseline

psychiatric

medication

comparison

disorders

and SSRIs

OCD and HC

excluded

All ≥ 20, 26.0 ± 4.0

All other axis I

Unmedicated

Baseline

psychiatric

≥ 10 weeks

comparison

disorders 22 HC

PRESS TR = 2000

Cho, Glx, Ins,

Software on

20x20x20mm

Lactate, Lipids,

Siemens

tNAA

scanner, areas

TE = 30

under the curve

NEX = 96

Cr ratios

JPRESS

rACC: 30x25x25mm

GABA, Glx

TR = 1500

OCD and HC

left DLPFC: TE = 68

excluded

Right DLPFC

10x48x20mm

Area under the

No

Higher Ins levels, lower Glx in OCD.

Yes

rACC: lower GABA in

curve peak

OCD, no differences

integration

Glx. No correlations with Y-BOCS.

Water scaling

NEX = 256 on and 256 off (rACC) and NEX = 512 on and 512 off (DLPFC) Simpson et al. (2015)

Adults

26.0 ± 3.0

15 OCD

Other axis I

Unmedicated

Baseline

psychiatric

≥ 6 weeks

comparison

disorders 16 HC

PRESS MRSI TR = 1500

OCD and HC

Right Caudate

Glu

Area under the

Yes

No differences Glu in all

Right Putamen

curve peak

regions. No correlations

Right Ventral striatum

integration

with Y-BOCS.

TE = 80

(except specific

Ratios relative

and social

NEX = 2

phobia)

Voxels within MRSI VOI:

to root-mean-

8x8x20mm

square of

excluded

background noise (SNR)

Wang et al. (2017)

Adults 15 OCD

21.9 ± 5.6

All other axis I

Unmedicated

Baseline

psychiatric

≥ 8 weeks

comparison

disorders

PRESS TR = 1500

rACC

Cho, Cr, Gln, Glu,

20x20x20mm

Ins, tNAA

LCModel Presumably

No

No significant differences all neurometabolites, Cho

15 HC

excluded

OCD and HC

TE = 35

water scaling

positive correlation FA.

NEX = 64 Wang et al. (2018)

Adults

22.85 ± 5.46

13 OCD

All other axis I

Unmedicated

Baseline

psychiatric

≥ 8 weeks

comparison

disorders 13 HC

PRESS TR = 1500

Thalamus

Glx, Cho, Ins, tNAA

20x20x20mm

LCModel

No

Higher Cho in the right thalamus in OCD.

Cr ratios

OCD and HC TE = 35

excluded

NEX = 64 Weber et al. (2014)

Children

21.8 ± 5.5

Left ROI

Psychosis,

Psychotropic

Baseline

substance

naïve

comparison

abuse, bipolar-, 15 OCD

TR = 2500

Prefrontal WM left and right

Cho, Cr, Glu, Ins,

20x20x15mm

tNAA

LCModel

Yes

OCD. TE = 30 tNAA, Cr and Cho

eating disorders

NEX = 192

positive correlated to

excluded Right

Higher Cho and tNAA right prefrontal WM in

Water scaling

OCD and HC

conduct- and

17 HC

PRESS

CY-BOCS.

21.7 ± 2.33

ROI 14 OCD 18 HC Yucel et al. (2007)

Adults

16.3 ± 5.7

19 OCD 19 HC

All other axis I

11 received

Baseline

psychiatric

stable dose of

comparison

disorders

SSRIs

OCD and HC

PRESS TR = 3000

Cho, Cr, Glx, Ins,

hemisphere, afterwards

tNAA

LCModel

No

Trend lower Glx

6.5 cm3

medicated versus

NEX = 128 Yucel et al. (2008)

Adults 20 OCD 26 HC

19.6 ± 5.3

All other axis I

Psychotropic

Baseline

psychiatric

medication,

comparison

disorders

stable ≥ 4

excluded

weeks

PRESS TR = 3000

OCD and HC

unmedicated patients. dACC left and right

Cho, Cr, Glx, Ins,

rACC left and right

tNAA

3

6.5 cm TE = 30 dACC NEX = 64, rACC NEX = 128

Lower tNAA concentrations in OCD.

Water scaling

averaged values TE = 30

excluded

dACC – left and right

LCModel Water scaling

Yes

Bilateral rACC and left dACC lower Glx in female patients. dACC and rACC Glx positively correlated Y-BOCS in female patients.

No medication effects. Zhang et al. (2016)

Adults

All ≥ 3,

88 OCD

Mean ± SD =

76 HC

unknown

All other axis I

Unmedicated

Baseline

psychiatric

≥ 8 weeks

comparison

disorders

MEGA_PRESS TR = 1500

dACC:

GABA, Glx, tNAA

20x40x20mm

LCModel

No

GABA in OCD.

Water scaling

OCD and HC TE = 68

excluded

dACC: trend lower

rACC: lower GABA and rACC: 30x30x30mm

tNAA in OCD. GABA

dACC: NEX = 168

and tNAA negatively

on / 168 off rACC

correlated Y-BOCS.

NEX = 128 on/ 128 off

Zhu et al. (2015)

Adults

21.7 ± 5.3

13 OCD

All other axis I

Unmedicated

Baseline

psychiatric

≥ 2 months

comparison

disorders 13 HC

PRESS TR = 1500

OCD and HC

rACC

Cho, Glu, Glx, Ins,

left and right Thalamus

tNAA,

LCModel

No

OCD.

Cr ratios

20x20x20mm

Thalamus: lower Glu

TE = 35

excluded

rACC: lower Glu in

(right) and higher Cho in NEX = 64

OCD (left), negative correlation Glu and Glx with compulsivity.

Zurowski et al. (2012)

Adults 20 OCD 11 HC

All ≥ 16, 26.0 ± 3.4

Major

Unmedicated

Twice per week

depression,

≥ 4 weeks

50min CBT

schizophrenia

sessions for 3

and substance

months, total of

abuse excluded

24 sessions

PRESS TR = 3000

Right OFC Right Striatum rACC

TE = 30

Cho, Cr, Glu, Ins

LCModel

Yes

Absolute concentrations

20x20x20mm

NEX = 128

No significant differences before and after CBT, Ins negatively correlated with change Y-BOCS.

(C)Y-BOCS: (Child) Yale-Brown Obsessive-Compulsive Scale; (J)PRESS: (J-resolved) point resolved spectroscopy; ADHD: Attention deficit hyperactivity disorder; ASD: Autism spectrum disorder; CBT: Cognitive Behavioral Therapy; CHESS: Chemical Shift Selective Saturation; dACC: Dorsal anterior cingulate cortex; DLPFC: Dorsolateral prefrontal cortex; FA: Fractional anisotropy; GSH: Glutathione; HC: Healthy controls; LASER: Localized by adiabatic selective refocusing; NEX: Number of Excitations; OCD: Obsessive-compulsive disorder; OFC: Orbitofrontal cortex; PCC: Posterior cingulate cortex; PEPSI: Proton echo-planar spectroscopic imaging; rACC: Rostral anterior cingulate cortex; SSRI: Selective serotonin reuptake inhibitors; TD: Tourette disorder; TE: Echo time in ms; TR: Repetition time in ms; WM: White matter.

According to the NIH quality assessment questionnaire, fifteen articles were rated as ‘good’ (Brennan et al., 2016; Brennan et al., 2015; Hatchondo et al., 2017; Naaijen et al., 2017; Naaijen et al., 2018; O'Neill et al., 2016; O'Neill et al., 2017; Ortiz et al., 2015; Simpson et al., 2015; Simpson et al., 2012; Weber et al., 2014; Yucel et al., 2007; Yucel et al., 2008; Zhu et al., 2015; Zurowski et al., 2012), 6 articles as ‘fair’ (Fan et al., 2017; Kitamura et al., 2006; Moon et al., 2018; Park et al., 2017; Wang et al., 2017; Wang et al., 2018), and one study was rated ‘poor’ (Zhang et al., 2016b). Results are reported according to VOI, focusing on the rACC, dACC, striatum, thalamus and other brain regions, including the DLPFC, PCC and WM. Next, relations with symptom severity and treatment effects are described.

Figure 2. 1H-MRS voxel placement across studies. For each brain region, the placement of the 1H-MRS voxel is shown in the color corresponding to the specific study investigating that region. We extracted the voxel dimensions provided by the manuscripts, then scaled the voxel dimensions to match the size of the brain template overlays as and manually placed the scaled voxels according to the exemplary placements in the individual manuscripts. * Studies conducted in pediatric samples are indicated with an asterisk. † O’Neill et all 2017 used a larger MRSI voxel (indicated by the more transparent rectangles) which was subsequently divided in grid-based voxels (indicated by the smaller squares), only voxels containing >50% of FreeSurfer derived rACC and PCC tissue were included for analyses. Abbreviations: rACC, rostral anterior cingulate cortex; dACC, dorsal anterior cingulate cortex; PCC, posterior cingulate cortex; OFC, orbitofrontal cortex; DLPFC, dorsolateral prefrontal cortex.

3.1. Neurometabolite concentrations in the rostral anterior cingulate cortex The glutamate-glutamine cycle was investigated by five studies looking at adult OCD patients. Compared with healthy controls, lower Glu concentrations in the rACC were observed by Zhu et al. (2015) but not others (Brennan et al., 2015; O'Neill et al., 2016; Wang et al., 2017; Zurowski et al., 2012). There were also no between-group differences in Gln concentrations (Brennan et al., 2015; Wang et al., 2017). Results on Glx (the combined spectral peak of Glu and Gln) showed higher inconsistency with the majority of studies showing no differences compared with healthy controls (Brennan et al., 2015; Simpson et al., 2012; Zhang et al., 2016b; Zhu et al., 2015) while others reported higher (O'Neill et al., 2016) or lower Glx concentrations (Yucel et al., 2008). Two studies that investigated GABA concentrations showed lower rACC concentrations in adult OCD patients compared to controls (Simpson et al., 2012; Zhang et al., 2016b). Zhang et al. (2016b) showed lower tNAA concentrations in OCD patients, while most studies did not show abnormalities in tNAA, nor in Cho, Ins and Cr concentrations (Hatchondo et al., 2017; O'Neill et al., 2016; Wang et al., 2018; Yucel et al., 2007; Zhu et al., 2015; Zurowski et al., 2012). Also in pediatric OCD patients, MRS studies on the glutamate system have provided mixed results with one study finding higher Glu concentrations in OCD versus healthy controls (J. Naaijen et al., 2017), whereas others found no differences in Glu (O'Neill et al., 2017) and Glx (Ortiz et al., 2015) concentrations. The latter study, however, observed higher Glx concentrations in pediatric patients with a longer illness duration (>2 years) compared with those with a more recent onset. In summary, two studies independently demonstrated lower GABA concentrations in the rACC of adult OCD patients, but the results on other neurometabolites concentrations are mixed (Table 2).

3.2. Neurometabolite concentrations in the dorsal anterior cingulate cortex Six studies investigated neurometabolite concentrations in the dACC of adult OCD patients versus controls. No neurometabolite abnormalities were found for Glu (Fan et al., 2017; O'Neill et al., 2016) or Gln (Fan et al., 2017). Conversely, Yucel et al. (2008) demonstrated lower Glx concentrations in female OCD patients compared with controls, whereas other studies did not observe such differences (O'Neill et al., 2016; Yucel et al., 2007; Zhang et al., 2016b). One study showed a trend for lower GABA concentrations (Zhang et al., 2016b). Except for one study that reported lower tNAA concentrations in OCD compared with healthy controls (Yucel et al., 2007), no differences were observed for Cho, Ins or Cr (Fan et al., 2017; Kitamura et al., 2006; O'Neill et al., 2016; Yucel et al., 2007; Yucel et al., 2008; Zhang et al., 2016b). Thus studies focusing on neurometabolite alterations in adult OCD in the dACC show no clear abnormalities.

3.3. Neurometabolite concentrations in the striatum Two studies investigated neurometabolite concentrations in the ventral striatum of adult OCD patients, but did not detect any between-group differences in Glu, Cho, Ins and Cr concentrations (Simpson et al., 2015; Zurowski et al., 2012). Glu was also not altered in the caudate nucleus or putamen (Simpson et al., 2015). One study found higher tNAA and Cho concentrations in the striatum of adult OCD patients (Hatchondo et al., 2017), but this was not consistent with a previous study which looked at the basal ganglia (Kitamura et al., 2006). Pediatric OCD patients also showed no differences in Glu and tNAA concentrations compared with healthy controls (Naaijen et al., 2017; Naaijen et al., 2018). Overall, no differences in neurometabolite concentrations are observed between OCD patients and controls (Table 2). It is important to mention that 1H-MRS in the striatum is limited by iron depositions in this area, leading to magnetic field inhomogeneities, reduced signal intensity and therefore lower 1H-MRS spectrum quality (Soreni et al., 2006; Vymazal et al., 1995).

3.4. Neurometabolite concentrations in the thalamus One study found lower Glu concentrations in the thalamus of adult OCD patients compared with controls (Zhu et al., 2015), while two other studies found no differences (Fan et al., 2017; O'Neill et al., 2016). Also, no differences in Gln (Fan et al., 2017) or Glx concentrations were observed (O'Neill et al., 2016; Wang et al., 2018; Zhu et al., 2015). Furthermore, there were also no betweengroup differences in tNAA, Ins and Cr concentrations in adult OCD patients (Fan et al., 2017; Hatchondo et al., 2017; Kitamura et al., 2006; O'Neill et al., 2016; Wang et al., 2018; Zhu et al., 2015). Results on Cho in the thalamus were mixed with four studies reporting higher concentrations in adult OCD (Hatchondo et al., 2017; Wang et al., 2018; Zhu et al., 2015), of which one on trendlevel (Fan et al., 2017) and two studies showing no differences in OCD patients (Kitamura et al., 2006; O'Neill et al., 2016). These results indicate that there might be cholinergic (Cho) abnormalities in the thalamus of adult OCD patients. Other neurometabolites show no consistent differences between patients and controls. No 1H-MRS studies in children focused on the thalamus.

3.5. Neurometabolite concentrations in other brain regions Three studies focused on the DLPFC in adult OCD patients. Simpson et al. (2012) found no differences in Glx or GABA concentrations. Conversely, two other studies demonstrated higher (Park et al., 2017) and lower (Moon et al., 2018) Glx concentrations in the DLPFC. Additionally, lower tNAA and Cho concentrations (Moon et al., 2018) and higher Ins concentrations (Park et al., 2017) were found in the same region in OCD patients. A possible explanation for these inconsistencies could be the limited overlap in voxel placement between the studies (Figure 2).

Two studies focused on the PCC, but no abnormalities were found in both pediatric (O'Neill et al., 2017) and adult OCD patients (Brennan et al., 2016). There were also no abnormalities in the OFC (Zurowski et al., 2012). Lastly, a few studies investigated the neurometabolite concentrations in WM. Kitamura et al. (2006) found no abnormalities for tNAA and Cho in the frontal WM in adult OCD patients, however, higher tNAA and Cho were reported in this region in pediatric OCD patients (Weber et al., 2014). No Glu, Ins and Cr differences have been reported in pediatric OCD patients versus controls (Weber et al., 2014). In the parietal WM also higher concentrations of Cho and a trend for higher tNAA concentrations were reported in adult OCD patients (Kitamura et al., 2006). In summary, various studies showed neurometabolite abnormalities in the DLPFC, but results are inconsistent. No abnormalities were found in the PCC and OFC and reported WM alterations warrant replication.

3.6. Associations between neurometabolite concentrations and symptom severity Sixteen studies (13 in adult and three in pediatric OCD) have looked into the correlation between neurometabolite concentrations and symptom severity, measured by (C)Y-BOCS scores, and severity measures for anxiety and depression. In adult patients, studies reported a positive correlation between Y-BOCS score and Cho concentrations in the parietal WM (Kitamura et al., 2006) or with Glx in the rACC and dACC of female OCD patients (Yucel et al., 2008). Two others reported negative correlations between Y-BOCS and Cr and Cho concentrations in the rACC (O'Neill et al., 2016), or GABA and tNAA in the rACC (Zhang et al., 2016b). Zhu et al. (2015) reported a negative correlation between the severity of compulsions and thalamic Glx. Other studies found no significant associations between neurometabolite concentrations and Y-BOCS scores (Brennan et al., 2016; Hatchondo et al., 2017; Simpson et al., 2015; Simpson et al., 2012). In pediatric OCD patients, a positive correlation with CY-BOCS was found for Ins, Cr, and tNAA in the right prefrontal WM

(Weber et al., 2014). Naaijen et al. (2017) did not observe a correlation between CY-BOCS scores and rACC Glu concentrations in pediatric patients. In adult patients anxiety scores correlated positively with thalamic Glu (Fan et al., 2017), and negatively with tNAA concentrations in the rACC (Zhang et al., 2016b). Severity of depression correlated negatively with Cho and Cr concentrations in both the rACC and dACC (O'Neill et al., 2016). Overall, multiple studies showed correlations between neurometabolite concentrations in various brain regions and severity of OCD symptoms or comorbid symptoms of anxiety and depression. In part because of heterogeneous VOIs and studied neurometabolites, no consistent pattern can be discerned on the basis of these studies.

3.7. CBT and medication effects on neurometabolite concentrations in OCD Only two studies focused on treatment-induced alterations in neurometabolite concentrations. In the study from O'Neill et al. (2017), 1H-MRS scans were acquired before and after 12-14 weekly CBT sessions in pediatric OCD patients. At baseline measurement, no between-group differences in Glu concentrations were detected. After CBT, Glu concentrations decreased in the rACC but not in the PCC. Glu concentrations in the PCC before treatment correlated positively with the treatmentinduced change of CY-BOCS scores (O'Neill et al., 2017). In a study examining adult OCD patients, where patients received 24 CBT sessions (twice weekly), no differences in Glu, Cho, Cr and Ins concentrations in the rACC, OFC and striatum were found before or after CBT between patients and healthy controls (Zurowski et al., 2012). However, Ins concentrations in the OFC correlated negatively with the treatment-induced change of Y-BOCS scores. Seven studies examined medication effects by comparing medicated and unmedicated OCD patients using cross-sectional designs. The study of O'Neill et al. (2016) showed that medicated (compared with unmedicated) patients had lower Glu, Glx, Cr, Ins and Cho concentrations in the

dACC, but not thalamus. Four other studies in adult medicated (versus unmedicated) OCD patients did not observe significant differences in Cho, Cr, GABA, Gln, Glu, Glx, Ins and tNAA concentrations in the dACC or rACC (Brennan et al., 2016; Brennan et al., 2015; Yucel et al., 2007; Yucel et al., 2008). However, a trend for lower Glx concentrations in the dACC of medicated (versus unmedicated) patients was found (Yucel et al., 2007). Also in pediatric patients, no medication effects were reported (Naaijen et al., 2017; Ortiz et al., 2015). In summary, as only two studies focused on the effect of cognitive behavioral treatment on neurometabolite concentrations, no strong conclusions can be drawn. Cross-sectional studies on medication status also do not provide strong evidence for medication effects, but future studies should use a longitudinal design, also taking into account medication type, dosage and duration.

Adult OCD patients Brain region

Glu

Gln

Glx

GABA

tNAA

Cho

Ins

Cr

rACC

↓====

==

↓↑ = = = =

↓↓

↓======

======

=====

=====

dACC

==

=

↓===

↓*

↓=====

=====

====

====

=

=

Striatum Ventral striatum

==

Caudate

=

Putamen

=

Thalamus

↓==

=

DLPFC PCC

=

OFC

=

=

===

↑=

↑=

=======

↑↑↑↑* = =

====

= ===

↓↑ =

=

↓=

↓=

↑=

=

=

=

=

=

=

=

=

↑* =

WM

↑=

Pediatric OCD patients Brain region

Glu

rACC

↑=

Striatum

==

PCC

=

WM

=

Gln

Glx =

GABA

tNAA

Cho

Ins

Cr

=

=

↓

=

↑

=

=

=

↑

Table 2. Overview of neurometabolite differences between OCD patients and controls.

↓: lower concentration compared to controls, ↑: higher concentration compared to controls, ↓* and ↑*: trend for lower and higher concentrations in OCD, respectively, =: no significant difference. Each symbol signifies a separate result.

4. Discussion This systematic review included 22 articles to identify alterations in neurometabolite concentrations in both pediatric and adult OCD patients using 3T 1H-MRS. As the number of studies focusing on pediatric patients and on the effect of treatment was limited, no strong conclusions can be drawn based on those findings. The results in adult patients differed greatly between studies. No neurometabolite alterations, as well as both higher and lower concentrations were found in adult OCD patients compared to controls. The most consistent findings were a lower GABA concentration in the rACC and higher Cho in the thalamus of OCD patients compared with healthy controls. The findings also suggests a relationship between neurometabolite concentrations and symptom severity in OCD patients, but the directionality of this association was not consistent across studies and might be dependent on the neurometabolite, brain region and sample characteristics. Studies on medication status, limited by the cross-sectional designs, did also not show consistent findings. Lower GABA concentrations were found in the rACC of OCD patients versus controls and also a trend for lower GABA concentrations was found in the dACC. However, the GABA abnormality detected by Zhang et al. (2016b) should be interpreted with caution as we rated this study as ‘poor’ according to the NIH Quality Assessment, due to the fact that the mean Y-BOCS score of the included patients was not stated and the Y-BOCS cutoff was low (≥3). Because lower MRI field strength makes it difficult to separate the spectral peaks of GABA from Glu and Gln, previous studies may not have been sensitive enough to measure GABA concentrations in OCD. Reduced GABA concentrations were also reported in other psychiatric disorders, including panic disorder (Ham et al., 2007) and major depressive disorder (Hasler et al., 2007). As GABA is mostly found intracellular (Petroff, 2002), lower concentrations might reflect a reduced number of GABAergic neurons. Not only the number of inhibitory neurons, but also altered GABAergic transmission might be of importance in OCD. This is shown by Zai et al. (2005) who reported dysfunction of the GABA B receptor 1 (GABBR1), suggesting impaired neurotransmission in OCD. It should also be noted that it remains challenging to detect a decrease of a metabolite that is

already difficult to detect. Therefore, replication of lower GABA concentrations in OCD is warranted, preferably using spectroscopy at ultra-high field strength scanners (≥7T). Two studies revealed significantly higher Cho concentrations in the thalamus of adult OCD patients versus controls (Hatchondo et al., 2017; Wang et al., 2018) (Table 2). Also a trend for higher Cho concentrations was detected (Fan et al., 2017). Higher thalamic Cho concentrations were previously observed in OCD patients that did not respond to treatment compared to those that did, but no differences with healthy controls were found (Mohamed et al., 2007). Higher thalamic Cho concentrations have, however, been reported previously in pediatric OCD patients (Rosenberg et al., 2001; Smith et al., 2003). Structural abnormalities of the thalamus indicate that this region is of importance in pediatric OCD (Boedhoe et al., 2017), but our results also reveal a role for the thalamus in adult OCD that should be further investigated. Higher Cho concentrations have also been found in adult patients with other brain disorders such as Alzheimer’s disease (Meyerhoff et al., 1994) and around the lesions in multiple sclerosis (Arnold et al., 1992). Cho concentrations are thought to reflect membrane turnover (Brennan et al., 2013), and future research should investigate to what extent Cho and myelination are involved in OCD (Bora et al., 2011; Fan et al., 2012). Both positive and negative associations between neurometabolite concentrations and symptom severity have been shown by eight studies. These contradictory findings might result from differences in sample characteristics, 1H-MRS quantification methods and brain regions investigated (Starck et al., 2008). Symptom improvement after treatment was also correlated with neurometabolite concentrations (O'Neill et al., 2017; Zurowski et al., 2012), however four studies found no association between neurometabolites and OCD symptom improvement. These findings might implicate a modulating effect of neurochemicals on symptom severity and treatment response, however the direction of this modulation remains unclear and should be further investigated.

4.1. Methodological considerations

The studies included in this review were very heterogeneous, making it hard to compare results and identify the source of inconsistencies. First of all, included studies used a variety of MRS acquisition techniques to assess metabolite levels (Table 1.). Different techniques may result in varying quantification of metabolite levels which is especially relevant for metabolites with similar structures, such as Glu and Gln, which are difficult to quantify separately, particularly when magnetic field homogeneity is lower, such as in subcortical regions (Ramadan et al., 2013). Second, different quantification methods were used to calculate the neurometabolite concentrations, including Cr ratios and values based on water scaling. In both cases, concentrations depend on the amount of gray and white matter in the voxel (Schuff et al., 2001). Therefore, the wide variety in voxel size and voxel placement across studies could have contributed to the observed inconsistencies (Figure 2). Furthermore, the assumption that Cr concentrations are stable in psychiatric and healthy states may be incorrect and could lead to biased results and misinterpretations of neurometabolite concentrations (Li et al., 2003). Although no Cr abnormalities were detected in OCD based on 3T MRS studies, previous research using 1.5T has shown Cr concentration abnormalities in OCD patients (Whiteside et al., 2012) and other psychiatric disorders such as bipolar depression and schizophrenia (Frye et al., 2007; Ongur et al., 2009). Over half of reviewed studies included medicated patients. Three out of 22 studies included patients on SSRIs only, 11 out of 22 studies included patients on SSRIs and/or other psychotropic medication, seven out of 22 studies included medication-free patients and one out of 22 included medication-naïve patients. Although we initially planned to exclude the studies with patients using pharmacologic interventions other than SSRIs or SNRIs (as pre-registrated in PROSPERO), we finally decided to keep these studies in the review and to address possible medication-related effects on metabolite levels. Although in general no medication effects were observed in the individual studies, we found a possible effect of medication on thalamic Cho concentrations. Out of three studies that observed increased Cho in the thalamus two studies used a non-medicated sample (Wang et al., 2018; Zhu et al., 2015) and one a medicated sample (Hatchondo et al., 2017). Interestingly, three other studies which had medicated samples did not show increased thalamic Cho levels (Fan et al.,

2017; Kitamura et al., 2006; O'Neill et al., 2016). The lower GABA in the rACC of OCD patients, was reported by only two studies which both included non-medicated samples. For other metabolites the findings are too inconsistent to reliable detect possible medication effects. The included studies also varied according to whether or not patients suffered from a comorbid disorder. Psychiatric disorders such as major depressive disorder and attention-deficit hyperactivity disorder (ADHD) are known to affect neurometabolite concentrations (Maltezos et al., 2014; Sanacora et al., 2004). Therefore, reported neurometabolite alterations in patients might not specific for OCD, but may rather be a result of a combination of OCD and comorbid disorders. The great variation in methodological aspects could explain the wide variety and the low reproducibility of the results. Because of this heterogeneity, we were not able to perform a metaanalysis and did therefore not find any consistent neurometabolite alterations in OCD over the included studies.

5. Conclusion Because of the heterogeneity and the inconsistent results, no strong evidence is found for OCD specific neurometabolite abnormalities. The number of studies focusing on pediatric OCD patients and on the effect of treatment was limited, therefore no conclusions can be drawn from those data. In adult patients, lower GABA in the rACC and higher Cho in the thalamus, as well as several associations with symptom severity were found. However, as various studies found no alterations in OCD patients compared to controls, more research with high field strength and dynamic 1H-MRS is needed to increase the detection of neurometabolite alterations and neurometabolite changes over time. This should give more insight in the possible role of neurochemistry in OCD.

Conflict of interest: None. Acknowledgements: The authors would like to thank Anders Thorsen for proof-reading and providing feedback on the manuscript.

Role of funding sources: This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

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Highlights ‘Lack of strong evidence for neurometabolite alterations in obsessive-compulsive disorder’ •

Most studies show no neurometabolite alterations in OCD patients

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Lower GABA in the rostral anterior cingulate cortex and higher thalamic choline is found in OCD

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Several studies show associations between neurometabolites and OCD symptom severity

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Methodologic heterogeneity between studies leads to low comparability of results

Role of funding sources: No funding for this research was provided. Contributors: Eline L. Vester, Niels T. de Joode and Chris Vriend designed the study with the guidance of Odile A. van den Heuvel. Eline L. Vester conducted the systematic analysis and wrote the first draft of the manuscript. Petra J.W. Pouwels provided additional feedback on the MRS related technical details. All authors contributed to and approved the final manuscript. Conflict of interest: None. Acknowledgements: The authors would like to thank Anders Thorsen for proof-reading and providing feedback on the manuscript.