Abstract
Generalised anxiety disorder (GAD) is a common psychiatric illness characterised by selective morpho-functional brain alterations. The breath of neuroimaging studies investigating the neural basis of GAD is extensive; however, its pathophysiology is still largely unknown. Specifically for proton Magnetic Resonance Spectroscopy (¹H MRS) investigations, which have the aim of identifying differences in metabolite levels between conditions in key brain areas, often showed contrasting results. Indeed, there are selected ¹H MRS studies reporting deficits of key metabolites in GAD patients; however, collectively the literature remains mixed with respect to consistency of major findings. In this review, we evaluate published ¹H MRS studies on GAD with the final aim of providing a comprehensive overview of the extent of neurometabolic dysfunctions associated with GAD. Interestingly, the majority of the studies reviewed showed altered metabolite levels in the dorsolateral prefrontal cortex and hippocampus suggesting regional specificity. These results also provide evidence of the utility of ¹H MRS not only for elucidating the pathophysiology of neuropsychiatric diseases, but also for the identification of more beneficial and targeted pharmacological interventions. Additionally, future studies are warranted to overcome methodological differences observed across the studies.
Key words: Generalised anxiety disorder, magnetic resonance spectroscopy, metabolites, neurochemicals
Generalised anxiety disorder (GAD) is a common psychiatric disease characterised by specific physical and psychological symptoms, including persisting worry, irritability and fatigue (DSM5, American Psychiatry Association, 2013; Diwadkar et al. 2017). GAD causes high human suffering, which is poorly understood. With respect to neuroimaging studies, the exploration of putative biomarkers of this disease is still at an early stage (Terlevic et al. 2012). This is true especially for the application of proton Magnetic Resonance Spectroscopy (¹H MRS), which has the unique ability of providing important quantitative biochemical information in localised brain areas (Stanley, 2002). This can lead to identifying possible and more effective pharmacological treatments for GAD. The prominent 1H metabolites include N-acetyl-aspartate (NAA), a marker for neuronal density and functioning, glycerophosphocholine plus phosphocholine (GPC + PC), membrane phospholipid metabolites, and phosphocreatine and creatine (PCr + Cr), involved in energetic processes (Brambilla et al. 2002, 2012; Stanley et al. 2007).
In this review, we aimed at providing an overview of ¹H MRS studies carried out in GAD with the final goal of shedding light on the significance of the reported altered metabolite levels in this disorder. A bibliographic search on PUBMED on ¹H MRS studies in GAD was performed and the research terms used were ‘MRS’, ‘spectroscopy’, and ‘generalised anxiety disorder’. Studies were excluded if the publications: (a) included twin samples, (b) investigated GAD not in relation to healthy controls (HC) or (c) explored only white matter structures. In total, eleven papers met the inclusion criteria and are summarised in Table 1. Briefly, among the 11 studies retrieved, the majority employed a multi-voxel (N = 7) instead of a single-voxel (N = 4) ¹H MRS technique and a 1.5 T scanner (N = 6) instead of a 3 T (N = 4) or a 4 T (N = 1) scanner. Interestingly, all the ¹H MRS studies on GAD, except for two studies Abdallah et al. 2012a; Strawn et al. 2013), focused on brain regions within the hippocampus and dorsolateral prefrontal cortex (DLPFC).
Table 1.
Selection of studies on generalised anxiety disorder exploring metabolic alterations with 1-H magnetic resonance spectroscopy
| Study | Sample (age, mean ± s.d.) | Gender F/M | Study design | Psychotropic medications | Method | Location (voxel size) | Quantification and reported 1H metabolites | ¹H MRS findings |
|---|---|---|---|---|---|---|---|---|
| Mathew et al. (2004) | GAD patients = 15 (39.3 ± 13.3) HC = 15 (39.1 ± 13.5) |
GAD patients = 8/7 HC = 8/7 |
Cross-sectional | Six medication-naïve. No psychotropic drugs within at least 4 weeks |
Multi-voxel 1H MRSI with TE = 280 ms at 1.5 T | Left and right hippocampus and DLPFC (1.5×0.75 × 0.75 cm3) | Metabolite ratio NAA/PCr+Cr GPC+PC |
|
| Mathew et al. (2008) | GAD patients = 14 (31.7 ± 9.6) HC = 7 (27.4 ± 4.2) |
GAD patients = 8/6 HC = 5/2 |
Longitudinal | Six medication- naïve. No current psychotropic drugs |
Multi-voxel 1H MRSI with TE = 280 ms at 1.5 T. 8 weeks of therapy with Riluzole |
Left and right hippocampus (1.13 cm3) | Absolute relative to water NAA PCr+Cr GPC+PC |
|
| Abdallah et al. (2012a) | GAD patients = 14 (33.9 ± 2.7) HC = 10 (30.3 ± 2.4) |
GAD patients = 8/6 HC = 6/4 |
Longitudinal | Fourteen medication- free | Multi-voxel 1H MRSI with TE = 280 ms and MRI at 1.5 T. 8 weeks of therapy with Riluzole |
Left and right lateral occipital (1.13 cm3) | Absolute relative to water NAA |
|
| Abdallah et al. (2012b) | GAD patients = 18 (33.9 ± 2.7) HC = 10 (30.3 ± 2.4) |
GAD patients = 8/10 HC = 6/4 |
Longitudinal | Eighteen medication-free | Multi-voxel 1H MRSI with TE = 280 ms and MRI at 1.5 T. 8 weeks of therapy with Riluzole |
Left and right hippocampus (1.13 cm3) | Absolute relative to water NAA |
|
| Mathew et al. (2010) | GAD patients = 9 (41.7 ± 15.8) HC = 10 (37.1 ± 14.8) |
GAD patients = 4/5 HC = 4/10 |
Longitudinal | Four medication-naïve. No psychotropic drugs within at least 4 weeks |
Multi-voxel 1H MRSI with TE = 280 ms at 1.5 T. 12 weeks of therapy with Paroxetine |
Left and right hippocampus (1.5 × 0.75 × 0.75 cm3 or 0.84 cc) | Metabolite ratio NAA/PCr+Cr |
|
| Strawn et al. (2013) | GAD patients = 10 (14 ± 2.2) HC = 10 (14.5 ± 2.3) |
GAD patients = 6/4 HC = 6/4 |
Cross-sectional | No psychotropic drugs within at least five half-lives | Single-voxel 1H-MRS with TE = 30 ms at 4 T | ACC (2.2 × 2.2 × 2.2cm3) | Metabolite ratio Glu/PCr + Cr |
|
| Raparia et al. (2016) | GAD patients = 16 (37.9 ± 14.2) HC = 16 (35.3 ± 10.3) |
GAD patients = 11/5 HC = 10/6 |
Cross-sectional | No medication for at least 2 weeks prior the MRSI scan | Multi-voxel 1H-MRSI with TE = 280 ms at 3 T | mPFC PMC SCC (7.5 × 7.5 × 15 mm3) | Absolute relative to water NAA PCr + Cr GPC + PC |
|
| Moon & Jeong (2016a) | GAD patients = 14 (36.6 ± 8.8) HC = 14 (37.8 ± 7.8) |
GAD patients = 8/6 HC = 8/6 |
Cross-sectional | Eleven patients with Anxiolytics and/or antidepressants. Three patients with single psychiatric medication comprising escitalopram or bupropion |
Single-voxel 1H-MRS with TE = 30 ms and MRI at 3 T | DLPFC (20 × 20 × 20 or 8 cm3) | Metabolite ratio NAA PCr + Cr GPC + PC Ml Lactate Lip α-Glx/ PCr + Cr β,γ-Glx/NAA |
|
| Moon et al. (2016b) | GAD patients = 13 (37.8 ± 7.6) HC = 13 (35.9 ± 3.5) |
GAD patients = 7/6 HC = 7/6 |
Cross-sectional | Seven patients with Anxiolytics and/or antidepressants. Six patients each were taking one psychotropic medication |
Single-voxel 1H-MRS with TE = 30 ms and fMRI at 3 T | DLPFC (20 × 20 × 20 or 8 cm3) | Metabolite ratio α-Glx/ PCr + Cr mI/ PCr + Cr GPC + PC/PCr + Cr β,γ-Glx/Cr NAA/Cr Lac/ PCr + Cr Lip/ PCr + Cr α-Glx/NAA mI/NAA GPC + PC/NAA β,γ-Glx/NAA PCr + Cr/NAA Lac/NAA Lip/NAA |
|
| Moon et al. (2015) | GAD patients = 15 (35.4 ± 9.6) HC = 15 (38.8 ± 8.9) |
GAD patients = 9/6 HC = 9/6 |
Cross-sectional | Ten patients with Anxiolytics and/or antidepressants. Five patients each were taking one psychotropic medication |
Single-voxel 1H-MRS with TE = 30 ms and MRI at 3 T | DLPFC (20 × 20 × 20 or 8 cm3) | Metabolite ratio NAA GPC + PC PCr + Cr Ml Lactate Lip α-Glx/ PCr + Cr β,γ-Glx/NAA |
|
| Coplan et al. (2014) | GAD patients = 29 (35.1 ± 11.9) HC = 22 (33.7 ± 10.4) |
GAD patients = 18/11 HC = 14/8 |
Cross-sectional | No medication | Multi-voxel 1H-MRSI with TE = 280 ms at 1.5 T | Left and right hippocampus (1.13 cm3) | Absolute relative to water NAA PCr + Cr GPC + PC |
|
GAD, Generalised anxiety disorder; MRI, Magnetic Resonance Imaging; fMRI, Functional Magnetic Resonance Imaging; MRS, Magnetic Resonance Spectroscopy; MRSI, Magnetic Resonance Spectroscopy Imaging; NAA, N-Acetyl-Aspartate; GPC + PC, Glycerophosphocholine plus Phosphocholine; PCr + Cr, Phosphocreatine plus Creatine; HC, Healthy controls; DLPFC, Dorsolateral prefrontal cortex; ACC, Anterior Cingulate Cortex; SSC, Somatosensory cortex; mPFC, medial prefrontal cortex; BMI, Body mass index; PSWQ, Penn State Worry Questionnaire.
Regarding the DLPFC, four studies of which three of them are from the same group, reported multiple contrasts including higher ratios of NAA/PCr + Cr (Mathew et al. 2004) and lower ratios of GPC + PC/PCr + Cr and GPC + PC/NAA (Moon et al. 2015; 2016b; Moon & Jeong, 2016a) ratios in GAD patients compared with HC. Additionally, Raparia et al. (2016) found higher NAA, PCr + Cr and GPC + PC levels in DLPFC, premotor cortex (PC) and secondary somatosensory cortex (SSC) bilaterally in GAD patients compared with HC. Interestingly, Mathew et al. (2004) reported that GAD patients with childhood abuse had higher NAA/PCr + Cr ratios compared with GAD patients without childhood abuse. In contrast, Raparia et al. (2016) found that GAD patients had no significant associations between emotional abuse scores and NAA, PCr + Cr and GPC + PC levels in DLPFC, PC and SSC bilaterally, but were significant in HC. Additionally, the three studies carried out by Moon et al. found that GPC + PC/PCr + Cr and GPC + PC/NAA ratios positively correlated with right DLPFC volumes (Moon & Jeong, 2016a; Moon et al. 2016b) and blood oxygenation level-dependent signal change in right DLPFC (Moon et al. 2016b). In contrast, a negative correlation was observed between GPC + PC/NAA ratio and anxiety symptom severity (Moon et al. 2015). Collectively, these studies suggest DLPFC neuronal deficits, which may in turn explain the neurocognitive deficits often observed in GAD patients. Indeed DLPFC is a key brain area regulating cognition and emotion, and plays a prominent role in working memory and executive brain functions (Brambilla et al. 2005).
Regarding the hippocampus, the study by Mathew et al. (2008) showed increased hippocampal NAA levels after 8 weeks of treatment with the glutamate-antagonist riluzole in GAD responder patients, whereas hippocampal NAA levels decreased over time in non-responders. Moreover, the change over time (post-minus pre treatment) in hippocampal volume was positively associated with change over time in NAA (especially in the right side) and with the improvement in anxiety symptoms (Abdallah et al. 2013). In contrast, lower ratios of NAA/PCr + Cr in bilateral hippocampus of nine GAD patients were not reversed after 12 weeks of paroxetine, despite marked symptoms improvement (Mathew et al. 2010). Additionally, Abdallah et al. (2012a) observed a negative correlation between right occipital NAA and symptoms improvement after riluzole treatment. Riluzole has been demonstrated to modulate extracellular glutamate through glial reuptake mechanisms regulating neural plasticity in the hippocampus (Frizzo et al. 2004). SSRIs have also been linked to enhance neural plasticity in hippocampal cells (Wang et al. 2008). Therefore, hippocampal NAA may reflect non-neuronal activity (Mathew et al. 2008) being a possible biomarker of GAD, and NAA change might be differently related to disparate mechanisms of drug action. Additionally, Coplan et al. (2014) also reported significant metabolites alterations associated with weight, with overweight GAD patients showing lower NAA in hippocampus compared with HC. Moreover, an inverse correlation was observed between hippocampal NAA and body mass index as well as higher worry predicted low hippocampal NAA and PCr + Cr. Lastly, Strawn et al. (2013) recently reported no significant alterations in glutamate/PCr + Cr ratios in the anterior cingulate of adolescents with GAD; however, a positive correlations between glutamate/PCr + Cr and anxiety symptoms severity.
In conclusions, these findings together suggest that GAD is associated with metabolic dysfunctions in selective brain regions, including the DLPFC and hippocampus. However, these results require further independent replications. Indeed, although the majority of the studies employed absolute metabolite values, some others used metabolite ratios, which might have therefore limited the interpretations of the results. Additionally, most of the studies were characterised by relatively small sample sizes and were carried out by the same research group, further decreasing the generalisability of their findings. Despite these limitations, these findings illustrate that alterations in specific metabolites, especially NAA, PCr + Cr and GPC + PC, might be considered putative biomarkers of GAD. Additionally, from the ¹H MRS studies here described emerged that pharmacological treatments positively interact with specific metabolites, especially NAA, within selective brain regions. Therefore, the investigation of brain metabolites could be very effective not only for elucidating the pathophysiology of neuropsychiatric diseases, but also for the identification of more beneficial and targeted pharmacological interventions. Finally, although ¹H MRS has been combined with other neuroimaging methods in recent studies (Abdallah et al. 2012a, b, 2013; Moon et al. 2015, 2016b; Moon & Jeong, 2016a), the evidence are still scarce. However, it is important to point out that the combination of more MRI methods allows the integration of different measures, which might increase the information and consequently the reliability of the findings.
Acknowledgements
None.
Financial support
This research received no specific grant from any funding agency, commercial or not-for-profit sectors.
Conflict of interest
None.
This Section of Epidemiology and Psychiatric Sciences appears in each issue of the Journal to stress the relevance of epidemiology for behavioral neurosciences, reporting the results of studies that explore the use of an epidemiological approach to provide a better understanding of the neural basis of major psychiatric disorders and, in turn, the utilisation of the behavioural neurosciences for promoting innovative epidemiological research.
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