Gray matter changes in panic disorder: A voxel-based meta-analysis and meta-analytic connectivity modeling

Cannabidiol in anxiety disorders: Current and future perspectives

Anxiety disorders are highly prevalent psychiatric disorders, characterized by a chronic course and often accompanied by comorbid symptoms that impair functionality and decrease quality of life. Despite advances in basic and clinical research in our understanding of these disorders, currently available pharmacological options are associated with limited clinical benefits and side effects that frequently lead to treatment discontinuation. Importantly, a significant number of patients do not achieve remission and live with lifelong residual symptoms that limit daily functioning. Since the 1970s, basic and clinical research on cannabidiol (CBD), a non-psychotomimetic compound found in the Cannabis sativa plant, has indicated relevant anxiolytic effects, garnering attention for its therapeutic potential as an option in anxiety disorder treatment. This chapter aims to review the history of these studies on the anxiolytic effects of CBD within the current understanding of anxiety disorders. It highlights the most compelling current evidence supporting its anxiolytic effects and explores future perspectives for its clinical use in anxiety disorders.

Grey matter structural alterations in anxiety disorders: a voxel-based meta-analysis

Anxiety disorders (ADs) are a group of prevalent and destructive mental illnesses, but the current understanding of their underlying neuropathology is still unclear. Employing voxel-based morphometry (VBM), previous studies have demonstrated several common brain regions showing grey matter volume (GMV) abnormalities. However, contradictory results have been reported among these studies. Considering that different subtypes of ADs exhibit common core symptoms despite different diagnostic criteria, and previous meta-analyses have found common core GMV-altered brain regions in ADs, the present research aimed to combine the results of individual studies to identify common GMV abnormalities in ADs. Therefore, we first performed a systematic search in PubMed, Embase, and Web of Science on studies investigating GMV differences between patients with ADs and healthy controls (HCs). Then, the anisotropic effect-size signed differential mapping (AES-SDM) was applied in this meta-analysis. A total of 24 studies (including 25 data sets) were included in the current study, and 906 patients with ADs and 1003 HCs were included. Compared with the HCs, the patients with ADs showed increased GMV in the left superior parietal gyrus, right angular gyrus, left precentral gyrus, and right lingual gyrus, and decreased GMV in the bilateral insula, bilateral thalamus, left caudate, and right putamen. In conclusion, the current study has identified some abnormal GMV brain regions that are related to the pathological mechanisms of anxiety disorders. These findings could contribute to a better understanding of the underlying neuropathology of ADs.

The difference in volumetric alternations of the orbitofrontal-limbic-striatal system between major depressive disorder and anxiety disorders: A systematic review and voxel-based meta-analysis

BACKGROUND

Major depressive disorder (MDD) and anxiety disorders (ANX) are psychiatric disorders with high mutual comorbidity rates that might indicate some shared neurobiological pathways between them, but they retain diverse phenotypes that characterize themselves specifically. However, no consistent evidence exists for common and disorder-specific gray matter volume (GMV) alternations between them.

METHODS

A systematic review and meta-analysis on voxel-based morphometry studies of patients with MDD and ANX were performed. The effect of comorbidity was explicitly controlled during disorder-specific analysis and particularly investigated in patient with comorbidity.

RESULTS

A total of 45 studies with 54 datasets comprising 2196 patients and 2055 healthy participants met the inclusion criteria. Deficits in the orbitofrontal cortex, striatum, and limbic regions were found in MDD and ANX. The disorder-specific analyses showed decreased GMV in the bilateral anterior cingulate cortex, right striatum, hippocampus, and cerebellum in MDD, while decreased GMV in the left striatum, amygdala, insula, and increased cerebellar volume in ANX. A totally different GMV alternation pattern was shown involving bilateral temporal and parietal gyri and left fusiform gyrus in patients with comorbidity.

LIMITATIONS

Owing to the design of included studies, only partial patients in the comorbid group had a secondary comorbidity diagnosis.

CONCLUSION

Patients with MDD and ANX shared a structural disruption in the orbitofrontal-limbic-striatal system. The disorder-specific effects manifested their greatest severity in distinct lateralization and directionality of these changes that differentiate MDD from ANX. The comorbid group showed a totally different GMV alternation pattern, possibly suggesting another illness subtype that requires further investigation.

Case report: Anxiety and depression as initial symptoms in a patient with acute hypoxia and patent foramen ovale

The prevalence of patent foramen ovale (PFO) is 15-35% among adults. The role of right-to-left shunting through the PFO, anxiety, depression, and hypoxemia in the systemic circulation remains poorly understood. Herein, we present the case of a 52-year-old woman with no heart or lung disease, who was admitted due to anxiety for 5 months and had symptom exacerbation with dizziness for 4 days and presented with cyanosis. She was noted to have acute hypoxemia, with an oxygen saturation of 94.48% on room air, and arterial blood gas showed an oxygen tension of 65.64 mmHg. Agitated saline contrast echocardiography showed right-to-left shunting due to PFO. Arteriovenous fistula, pneumonia, pulmonary embolism, pulmonary hypertension, congestion peripheral cyanosis, ischemic peripheral cyanosis, and methemoglobin were excluded. Additionally, the patient improved by taking Paroxetine, Oxazepam, and Olanzapine. Her oxygen tension returned to 90.42 mmHg, and her symptoms resolved. In the case of severe anxiety and depression, right-to-left shunting through the PFO may cause acute systemic hypoxemia via a flow-driven mechanism, occasionally manifesting as cyanosis. When anxiety improved, hypoxia also improved. Thus, the treatment of anxiety and depression seems effective in improving hypoxemia. Notably, this is a rare report, and we hope to draw the attention of psychosomatic specialists, psychiatrists, and clinicians to seek the relationship between anxiety appearing as acute stress and PFO. This may be a new therapeutic method for treating severe anxiety disorder.

Sleep Quality Disturbances Are Associated with White Matter Alterations in Veterans with Post-Traumatic Stress Disorder and Mild Traumatic Brain Injury

Sleep disturbances are strongly associated with mild traumatic brain injury (mTBI) and post-traumatic stress disorder (PTSD). PTSD and mTBI have been linked to alterations in white matter (WM) microstructure, but whether poor sleep quality has a compounding effect on WM remains largely unknown. We evaluated sleep and diffusion magnetic resonance imaging (dMRI) data from 180 male post-9/11 veterans diagnosed with (1) PTSD (n = 38), (2) mTBI (n = 25), (3) comorbid PTSD+mTBI (n = 94), and (4) a control group with neither PTSD nor mTBI (n = 23). We compared sleep quality (Pittsburgh Sleep Quality Index, PSQI) between groups using ANCOVAs and calculated regression and mediation models to assess associations between PTSD, mTBI, sleep quality, and WM. Veterans with PTSD and comorbid PTSD+mTBI reported poorer sleep quality than those with mTBI or no history of PTSD or mTBI (p = 0.012 to <0.001). Poor sleep quality was associated with abnormal WM microstructure in veterans with comorbid PTSD+mTBI (p < 0.001). Most importantly, poor sleep quality fully mediated the association between greater PTSD symptom severity and impaired WM microstructure (p < 0.001). Our findings highlight the significant impact of sleep disturbances on brain health in veterans with PTSD+mTBI, calling for sleep-targeted interventions.

Prediction of prognosis in patients with panic disorder using pre-treatment brain white matter features

BACKGROUND

The early identification of patients with panic disorder (PD) with a poor prognosis is important for improving treatment outcomes; however, it is challenging due to a lack of objective biomarkers. We investigated the reliability of characterizing structural white matter (WM) connectivity and its ability to predict PD prognosis after pharmacotherapy.

METHODS

A total of 138 patients (59 men) with PD and 153 healthy controls (HCs; 73 men) participated in this study. PD symptom severity was measured using the Panic Disorder Severity Scale (PDSS) at baseline and follow-up periods of 8 weeks, 6 months, and 1 year. The least absolute shrinkage and selection operator (Lasso) was utilized to identify prognosis-related WM regions on diffusion imaging features.

RESULTS

Lasso identified seven prognosis-related WM regions: the bilateral posterior corona radiata, bilateral posterior limb of the internal capsule, the left retrolenticular part of the internal capsule, the left sagittal stratum, and the right fornix/stria terminalis. Some of these regions showed lower mean fractional anisotropy (FA) values in patients with PD than in HCs. The predicted PDSS scores using FA from these regions consistently correlated with the actual prognosis in all periods.

LIMITATIONS

This study had limited ability to evaluate individual longitudinal changes in detail owing to the data acquisition time and brain atlas resolution.

CONCLUSIONS

Our findings suggest the possibility of using structural WM connectivity as a biomarker for the clinical characterization of PD. Our findings will expand our understanding of the neurobiology of PD and improve biomarker-based prognosis prediction in clinical practice.

The Computer Simulation for Triggering Anxiety in Panic Disorder Patients Modulates the EEG Alpha Power during an Oddball Task

Aim: The present study investigated the differences between the Panic Disorder (PD) patients groups’ and healthy controls for the EEG alpha dynamics under the frontal cortex and reaction time during the oddball task. Material and Methods: The reaction time during the oddball paradigm concomitant to EEG alpha power was tested in nine PD patients and ten healthy controls before and after a computer simulation presentation. Results: The findings revealed a decrease in EEG alpha power in PD patients concerning the control group (p ≤ 0.0125). However, both groups demonstrated an increased cortical oscillation after the computer simulation, except for the Fp1 electrode during M3 moment in the experimental group. The experimental group has a fast reaction time compared to healthy individuals during the oddball task (p = 0.002). Conclusions: We propose that the decrease in EEG alpha power in the PD patients may indicate an increase in processing related to an anxiogenic stimulus and interference of the anxiety state that compromises the inhibitory control. The reaction time task reveals cognitive symptoms in the experimental group, which may be related to the faster reactivity and high impulsivity to stimuli.

An interpretable radiomics model for the diagnosis of panic disorder with or without agoraphobia using magnetic resonance imaging

BACKGROUND

Early and accurate diagnosis of panic disorder with or without agoraphobia (PDA) is crucial to reducing disease burden and individual suffering. However, its diagnosis is challenging for lack of validated biomarkers. This study aimed to investigate whether radiomic features extracted from T1-weighted images (T1) of major fear-circuit structures (amygdala, insula, and anterior cingulate cortex [ACC]) could differentiate patients with PDA from healthy controls (HCs).

METHODS

The 213 participants (93 PDA, 120 HCs) were allocated to training (n = 149) and test (n = 64) sets after undergoing magnetic resonance imaging. Radiomic features (n = 1498) were extracted from T1 of the studied structures. Machine learning models were trained after feature selection and then validated in the test set. SHapley Additive exPlanations (SHAP) explored the model interpretability.

RESULTS

We identified 29 radiomic features to differentiate participants with PDA from HCs. The area under the curve, accuracy, sensitivity, and specificity of the best performing radiomics model in the test set were 0.84 (95% confidence interval: 0.74-0.95), 81.3%, 75.0%, and 86.1%, respectively. The SHAP model explanation suggested that the energy features extracted from the bilateral long insula gyrus and central sulcus of the insula and right ACC were highly associated with the risk of PDA.

LIMITATIONS

This was a cross-sectional study with a relatively small sample size, and the causality of changes in radiomic features and their biological and clinical meanings remained to be elucidated.

CONCLUSIONS

Our findings suggest that radiomic features from the fear-circuit structures could unveil hidden microstructural aberrations underlying the pathogenesis of PDA that could help identify PDA.

Glutamic Acid Decarboxylase 1 Gene Methylation and Panic Disorder Severity: Making the Connection by Brain Gray Matter Volume

OBJECTIVE

This study aimed to test the hypothesis that the relationship between glutamic acid decarboxylase (GAD) 1 gene methylation and severity of clinical symptoms of panic disorder (PD) is mediated by the effect of GAD1 gene methylation on gray matter volume (GMV) and the effect of GMV on PD.

METHODS

Panic disorder (n = 24) patients were recruited consecutively from the Affiliated Brain Hospital of Nanjing Medical University through outpatient and public advertising, eligible healthy controls (HCs) (n = 22) were recruited from public advertising. We compared GMV and GAD1 gene methylation in PD and HCs to estimate the differences, and on the basis of the relationship between gray matter volumes and GAD1 gene methylation in PD patients was evaluated, the role of GMV as a mediator of GAD1 gene methylation and PD clinical symptoms was analyzed.

RESULTS

Panic disorder patients had significantly lower methylation in the GAD1 promoter region on Cytosine-phosphate-guanine (CPG) 7 than HCs (t = 2.380, p = 0.021). Pearson correlation analysis found a significant negative association between cg171674146 (cg12) site and clinical severity (n = 24, r = -0.456, p = 0.025). Compared to HCs, patients with PD had decreased gray matter volumes in several brain regions, which were also associated with PD severity. Left postcentral gyrus (PoCG) GMV mediated the association between cg12 methylation and PD severity, and there was a significant mediation effect of right angular gyrus (ANG) gray matter volumes on the relationship between cg12 methylation and PD severity.

LIMITATION

No direct results can be derived for methylation patterns in different brain regions; the study is cross-sectional; relatively small size.

Asymmetry in the Central Nervous System: A Clinical Neuroscience Perspective

Recent large-scale neuroimaging studies suggest that most parts of the human brain show structural differences between the left and the right hemisphere. Such structural hemispheric asymmetries have been reported for both cortical and subcortical structures. Interestingly, many neurodevelopmental and psychiatric disorders have been associated with altered functional hemispheric asymmetries. However, findings concerning the relation between structural hemispheric asymmetries and disorders have largely been inconsistent, both within specific disorders as well as between disorders. In the present review, we compare structural asymmetries from a clinical neuroscience perspective across different disorders. We focus especially on recent large-scale neuroimaging studies, to concentrate on replicable effects. With the notable exception of major depressive disorder, all reviewed disorders were associated with distinct patterns of alterations in structural hemispheric asymmetries. While autism spectrum disorder was associated with altered structural hemispheric asymmetries in a broader range of brain areas, most other disorders were linked to more specific alterations in brain areas related to cognitive functions that have been associated with the symptomology of these disorders. The implications of these findings are highlighted in the context of transdiagnostic approaches to psychopathology.

Disrupted fronto-temporal function in panic disorder: a resting-state connectome study

Recent neuroimaging studies have identified alterations in activity and connectivity among many brain regions as potential biomarkers for panic disorder. However, the functional connectome of panic disorder is not well understood. Therefore, a graph-theoretical approach was applied in this study to construct functional networks of patients and healthy controls in order to discover topological changes in panic disorder. 31 patients and 33 age and sex matched healthy controls underwent resting-state functional magnetic resonance imaging. Brain networks for each participant were structured using nodes from the Anatomical Automatic Labeling template and edges from connectivity matrices. Then, topological organizations of networks were calculated. Network-based statistical analysis was conducted, and global and nodal properties were compared between patients and controls. Unlike controls, patients with panic disorder displayed a small-world network. Patients also revealed decreased nodal efficiency in right superior frontal gyrus (SFG), middle frontal gyrus (MFG), right superior temporal gyrus (STG), and left middle temporal gyrus (MTG). Decreased functional connectivity was found in panic disorder between right MTG and extensive temporal regions. Among these disrupted regions, the decreased nodal efficiency of SFG showed a positive correlation with clinical symptoms while nodal betweenness centrality in angular gyrus showed a negative correlation. Our results indicated decreased function of global and regional information transmission in panic disorder and emphasized the role of temporal regions in its pathology.

A review of systems biology research of anxiety disorders

The development of "omic" technologies and deep phenotyping may facilitate a systems biology approach to understanding anxiety disorders. Systems biology approaches incorporate data from multiple modalities (e.g., genomic, neuroimaging) with functional analyses (e.g., animal and tissue culture models) and mathematical modeling (e.g., machine learning) to investigate pathological biophysical networks at various scales. Here we review: i) the neurobiology of anxiety disorders; ii) how systems biology approaches have advanced this work; and iii) the clinical implications and future directions of this research. Systems biology approaches have provided an improved functional understanding of candidate biomarkers and have suggested future potential for refining the diagnosis, prognosis, and treatment of anxiety disorders. The systems biology approach for anxiety disorders is, however, in its infancy and in some instances is characterized by insufficient power and replication. The studies reviewed here represent important steps to further untangling the pathophysiology of anxiety disorders.

Intrinsic Network Brain Dysfunction Correlates With Temporal Complexity in Generalized Anxiety Disorder and Panic Disorder

Background: Generalized anxiety disorder (GAD) and panic disorder (PD) are the two severe subtypes of anxiety disorders (ADs), which are similar in clinical manifestation, pathogenesis, and treatment. Earlier studies have taken a whole-brain perspective on GAD and PD in the assumption that intrinsic fluctuations are static throughout the entire scan. However, it has recently been suggested that the dynamic alternations in functional connectivity (FC) may reflect the changes in macroscopic neural activity patterns underlying the critical aspects of cognition and behavior, and thus may act as biomarkers of disease. Methods: In this study, the resting-state functional MRI (fMRI) data were collected from 26 patients with GAD, 22 patients with PD, and 26 healthy controls (HCs). We investigated dynamic functional connectivity (DFC) by using the group spatial independent component analysis, a sliding window approach, and the k-means clustering methods. For group comparisons, the temporal properties of DFC states were analyzed statistically. Results: The dynamic analysis demonstrated two discrete connectivity "States" across the entire group, namely, a more segregated State I and a strongly integrated State II. Compared with HCs, patients with both GAD and PD spent more time in the weakly within-network State I, while performing fewer transitions and dwelling shorter in the integrated State II. Additionally, the analysis of DFC strength showed that connections associated with ADs were identified including the regions that belonged to default mode (DM), executive control (EC), and salience (SA) networks, especially the connections between SA and DM networks. However, no significant difference was found between the GAD and PD groups in temporal features and connection strength. Conclusions: More common but less specific alterations were detected in the GAD and PD groups, which implied that they might have similar state-dependent neurophysiological mechanisms and, in addition, could hopefully help us better understand their abnormal affective and cognitive performances in the clinic.

Anxiety disorders

Anxiety disorders form the most common group of mental disorders and generally start before or in early adulthood. Core features include excessive fear and anxiety or avoidance of perceived threats that are persistent and impairing. Anxiety disorders involve dysfunction in brain circuits that respond to danger. Risk for anxiety disorders is influenced by genetic factors, environmental factors, and their epigenetic relations. Anxiety disorders are often comorbid with one another and with other mental disorders, especially depression, as well as with somatic disorders. Such comorbidity generally signifies more severe symptoms, greater clinical burden, and greater treatment difficulty. Reducing the large burden of disease from anxiety disorders in individuals and worldwide can be best achieved by timely, accurate disease detection and adequate treatment administration, scaling up of treatments when needed. Evidence-based psychotherapy (particularly cognitive behavioural therapy) and psychoactive medications (particularly serotonergic compounds) are both effective, facilitating patients' choices in therapeutic decisions. Although promising, no enduring preventive measures are available, and, along with frequent therapy resistance, clinical needs remain unaddressed. Ongoing research efforts tackle these problems, and future efforts should seek individualised, more effective approaches for treatment with precision medicine.

Distinct grey matter volume alterations in adult patients with panic disorder and social anxiety disorder: A systematic review and voxel-based morphometry meta-analysis

BACKGROUND

The paradox of similar diagnostic criteria but potentially different neuropathologies in panic disorder (PD) and social anxiety disorder (SAD) needs to be clarified.

METHODS

We performed a qualitative systematic review and a quantitative whole-brain voxel-based morphometry (VBM) meta-analysis with an anisotropic effect-size version of seed-based D mapping (AES-SDM) to explore whether the alterations of grey matter volume (GMV) in PD are similar to or different from those in SAD, together with potential confounding factors.

RESULTS

A total of thirty-one studies were eligible for inclusion, eighteen of which were included in the meta-analysis. Compared to the respective healthy controls (HC), qualitative and quantitative analyses revealed smaller cortical-subcortical GMVs in PD patients in brain areas including the prefrontal and temporal-parietal cortices, striatum, thalamus and brainstem, predominantly right-lateralized regions, and larger GMVs in the prefrontal and temporal-parietal-occipital cortices, and smaller striatum and thalamus in SAD patients. Quantitatively, the right inferior frontal gyrus (IFG) deficit was specifically implicated in PD patients, whereas left striatum-thalamus deficits were specific to SAD patients, without shared GMV alterations in both disorders. Sex, the severity of clinical symptoms, psychiatric comorbidity, and concomitant medication use were negatively correlated with smaller regional GMV alterations in PD patients.

CONCLUSION

PD and SAD may represent different anxiety sub-entities at the neuroanatomical phenotypes level, with different specific neurostructural deficits in the right IFG of PD patients, and the left striatum and thalamus of SAD patients. This combination of differences and specificities can potentially be used to guide the development of diagnostic biomarkers for these disorders.

Biomarkers in Panic Disorder

Background:

Panic disorder (PD) is a kind of anxiety disorder that impacts the life quality and functional perspectives in patients. However, the pathophysiological study of PD seems still inadequate and many unresolved issues need to be clarified.

Objectives:

In this review article of biomarkers in PD, the investigator will focus on the findings of magnetic resonance imaging (MRI) of the brain in the pathophysiology study. The MRI biomarkers would be divided into several categories, on the basis of structural and functional perspectives.

Methods:

The structural category would include the gray matter and white matter tract studies. The functional category would consist of functional MRI (fMRI), resting-state fMRI (Rs-fMRI), and magnetic resonance spectroscopy (MRS). The PD biomarkers revealed by the above methodologies would be discussed in this article.

Results:

For the gray matter perspectives, the PD patients would have alterations in the volumes of fear network structures, such as the amygdala, parahippocampal gyrus, thalamus, anterior cingulate cortex, insula, and frontal regions. For the white matter tract studies, the PD patients seemed to have alterations in the fasciculus linking the fear network regions, such as the anterior thalamic radiation, uncinate fasciculus, fronto-occipital fasciculus, and superior longitudinal fasciculus. For the fMRI studies in PD, the significant results also focused on the fear network regions, such as the amygdala, hippocampus, thalamus, insula, and frontal regions. For the Rs-fMRI studies, PD patients seemed to have alterations in the regions of the default mode network and fear network model. At last, the MRS results showed alterations in neuron metabolites of the hippocampus, amygdala, occipital cortex, and frontal regions.

Conclusion:

The MRI biomarkers in PD might be compatible with the extended fear network model hypothesis in PD, which included the amygdala, hippocampus, thalamus, insula, frontal regions, and sensory-related cortex.

Focusing on Comorbidity-A Novel Meta-Analytic Approach and Protocol to Disentangle the Specific Neuroanatomy of Co-occurring Mental Disorders

BACKGROUND

In mental health, comorbidities are the norm rather than the exception. However, current meta-analytic methods for summarizing the neural correlates of mental disorders do not consider comorbidities, reducing them to a source of noise and bias rather than benefitting from their valuable information.

OBJECTIVES

We describe and validate a novel neuroimaging meta-analytic approach that focuses on comorbidities. In addition, we present the protocol for a meta-analysis of all major mental disorders and their comorbidities.

METHODS

The novel approach consists of a modification of Seed-based d Mapping-with Permutation of Subject Images (SDM-PSI) in which the linear models have no intercept. As in previous SDM meta-analyses, the dependent variable is the brain anatomical difference between patients and controls in a voxel. However, there is no primary disorder, and the independent variables are the percentages of patients with each disorder and each pair of potentially comorbid disorders. We use simulations to validate and provide an example of this novel approach, which correctly disentangled the abnormalities associated with each disorder and comorbidity. We then describe a protocol for conducting the new meta-analysis of all major mental disorders and their comorbidities. Specifically, we will include all voxel-based morphometry (VBM) studies of mental disorders for which a meta-analysis has already been published, including at least 10 studies. We will use the novel approach to analyze all included studies in two separate single linear models, one for children/adolescents and one for adults.

DISCUSSION

The novel approach is a valid method to focus on comorbidities. The meta-analysis will yield a comprehensive atlas of the neuroanatomy of all major mental disorders and their comorbidities, which we hope might help develop potential diagnostic and therapeutic tools.

A meta-analytic approach to mapping co-occurrent grey matter volume increases and decreases in psychiatric disorders

Numerous studies have investigated grey matter (GM) volume changes in diverse patient groups. Reports of disorder-related GM reductions are common in such work, but many studies also report evidence for GM volume increases in patients. It is unclear whether these GM increases and decreases are independent or related in some way. Here, we address this question using a novel meta-analytic network mapping approach. We used a coordinate-based meta-analysis of 64 voxel-based morphometry studies of psychiatric disorders to calculate the probability of finding a GM increase or decrease in one region given an observed change in the opposite direction in another region. Estimating this co-occurrence probability for every pair of brain regions allowed us to build a network of concurrent GM changes of opposing polarity. Our analysis revealed that disorder-related GM increases and decreases are not independent; instead, a GM change in one area is often statistically related to a change of opposite polarity in other areas, highlighting distributed yet coordinated changes in GM volume as a function of brain pathology. Most regions showing GM changes linked to an opposite change in a distal area were located in salience, executive-control and default mode networks, as well as the thalamus and basal ganglia. Moreover, pairs of regions showing coupled changes of opposite polarity were more likely to belong to different canonical networks than to the same one. Our results suggest that regional GM alterations in psychiatric disorders are often accompanied by opposing changes in distal regions that belong to distinct functional networks.