Emotion processing in depression with and without comorbid anxiety disorder

Left Insula and Right Middle Temporal Gyrus Dominate Cortical Network Discriminating Arousal-dependent Emotions

Emotion processing is an integral part of everyone's life. The basic neural circuits involved in emotion perception are becoming clear, though the emotion's cognitive processing remains under investigation. Utilizing the stereo-electroencephalograph with high temporal-spatial resolution, this study aims to decipher the neural pathway responsible for discriminating low-arousal and high-arousal emotions. This study involves 19 patients with pharmacologically resistant epilepsy who participate in a delayed match/mismatch sample task designed to separately assess their ability to discriminate between low-arousal and high-arousal emotions. Three groups of 11 brain subregions, with dominant lateralization, compose a network, which is identified as responsible for discriminating arousal-dependent emotions. The connection of these subregions, leading by the left insula and right middle temporal gyrus, defines the pathways for discriminating emotions with different arousals. Further, the separated network patterns related to emotional discrimination are face-independent. Overall, the left insula and the right middle temporal gyrus emerge as core components in the network, which plays key roles in the dynamic course for discriminating low- and high-arousal emotions in the human brain.

Shared and distinctive changes of the white matter integrity in generalized anxiety disorder with or without depressive disorder

BACKGROUND

Generalized anxiety disorder (GAD) is a prevalent anxiety disorder often comorbid with major depressive disorder (MDD). Previous neuroimaging studies have shown that white matter (WM) microstructural alterations are critical for efficient communication between brain regions, and play an important role in the pathology of GAD. However, the exact profile of WM abnormalities in GAD with and without comorbid MDD remain unclear. This study aimed to uncover them using a novel global probabilistic tractography technology named Tracts Constrained by Underlying Anatomy (TRACULA), and to assess the correlations between fascicle integrity and symptom severity.

METHODS

We recruited 20 pure GAD (p-GAD) patients, 14 GAD comorbid with MDD (GAD + MDD) patients, and 41 age- and sex-matched healthy controls (HCs). All participants underwent T1 magnetic resonance imaging and diffusion tensor imaging. For each subject, 42 WM fiber bundles of the whole brain were successfully tracked and calculated with five metrics including volume, fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD) and axial diffusivity (AD). Group comparison were firstly performed between the whole GAD patients and HCs. Then, we compared the differences among the three groups (the p-GAD, GAD + MDD patients and HCs) using the one-way ANCOVA and post hoc analysis with the Bonferroni correction. Furthermore, correlations between abnormal WM metrics and clinical symptom severity were examined using partial correlations analyses among patients.

RESULTS

Compare to HCs, both p-GAD and GAD + MDD patients exhibited decreased FA values in left superior longitudinal fasciculus (SLF) II, and right dorsal of cingulum bundle (CBD); Moreover, GAD + MDD patients showed decreased FA, increased MD and RD values in the central and temporal section of the body of the corpus callosum (CC-BODY), right SLF I and II compared to HCs. Within the GAD + MDD group, GAD-7 scores were negatively correlated with FA values (r = -0.75, p = 0.008) and positively correlated with RD values (r = 0.7, p = 0.017) in the right CBD.

CONCLUSION

This study identified both shared and distinctive changes in GAD patients with and without MDD. The shared WM disruption in the p-GAD and GAD + MDD groups located in the left SLF and right CBD, while only GAD + MDD patients showed distinctive changes in the central and temporal sections of the CC-BODY and right SLF. Current study gave a comprehensive characterization of WM abnormalities among these patients, and highlighted TRACULA's value in identifying critical WM changes.

Neurobiological correlates of comorbidity in disorders across the affective disorders-psychosis spectrum

Disorders across the affective disorders-psychosis spectrum such as major depressive disorder (MDD), bipolar disorder (BD), schizoaffective disorder (SCA), and schizophrenia (SCZ), have overlapping symptomatology and high comorbidity rates with other mental disorders. So far, however, it is largely unclear why some of the patients develop comorbidities. In particular, the specific genetic architecture of comorbidity and its relationship with brain structure remain poorly understood. Therefore, we performed systematic analyses of clinical, genetics and brain structural measures to gain further insights into the neurobiological correlates of mental disorder's comorbidity. We investigated a sub-sample of the Marburg/Münster Cohort Study (MACS), comprising DSM-IV-TR diagnosed patients with a single disorder in the affective disorders-psychosis spectrum (SD, n = 470, MDD; BD; SCA; SCZ), with additional mental disorder's comorbidities (COM, n = 310), and healthy controls (HC, n = 649). We investigated group differences regarding a) the global severity index (based on SCL90-R), b) a cross-disorder polygenic risk score (PRS) calculated with PRS-continuous shrinkage (PRS-CS) using the summary statistics of a large genome-wide association study across mental disorders, and c) whole brain grey matter volume (GMV). The SCL90-R score significantly differed between groups (COM > SD > HC). While SD and COM did not differ in cross-disorder PRS and GMV, SD and COM versus HC displayed increased cross-disorder PRS and decreased GMV in the bilateral insula, the left middle temporal, the left inferior parietal, and several frontal gyri. Our results thus suggest that disorders in the affective disorders-psychosis spectrum with or without additional comorbidities differ in self-reported clinical data, but not on genetic or brain structural levels.

Resting-State Brain Dynamics Unique to Anxiety in Major Depressive Disorder

Background

Major depressive disorder with anxiety (MDD-A) is considered as a clinical subphenotype of major depressive disorder (MDD). There continues to be debate regarding the legitimacy of differentiating between the two diagnoses and their neurobiological foundations, given that the symptoms of MDD and MDD-A overlap. However, there is still a dearth of research that delineates the dynamic alteration in the brain activity unique to anxiety in MDD with resting-state functional magnetic resonance imaging (R-fMRI).

Methods

30 patients with MDD, 45 patients with MDD-A, and 46 healthy controls completed R-fMRI scans. Dynamic analysis was utilized to generate many widely used measures, such as voxel-mirrored homotopic connectivity, global signal correlation, regional homogeneity, amplitude of low-frequency fluctuations, and network degree centrality. Concordance between these indices was assessed with Kendall's W coefficient for both volume and voxel-wise concordance. Finally, the differences in voxel-wise concordance among the groups were looked at, and their relationship to clinical factors was assessed.

Results

Compared to the healthy control group, both MDD and MDD-A exhibited decreased dynamic R-fMRI indices in the bilateral calcarine, left postcentral gyrus, inferior parietal lobe, right lingual gyrus, and middle occipital gyrus. In comparison to the MDD group, the MDD-A group displayed a reduction in voxel-wise concordance in the left medial superior frontal gyrus. Furthermore, it was observed that the MDD and MDD-A groups both exhibited a negative correlation between anxiety levels and voxel-wise concordance in the left medial superior frontal gyrus.

Conclusions

The aberrant voxel-wise concordance of the left medial superior frontal gyrus may differentiate the neurobiological aspects of MDD with anxiety symptom from MDD. These findings indicate the underlying mechanisms implicated in MDD with anxiety symptom while highlighting the significance of accounting for heterogeneity in depression research.

Shared and distinctive neural substrates of generalized anxiety disorder with or without depressive symptoms and their roles in prognostic prediction

BACKGROUND

The neurophysiological mechanisms underlying generalized anxiety disorder (GAD) with or without depressive symptoms are obscure. This study aimed to uncover them and assess their predictive value for treatment response.

METHODS

We enrolled 98 GAD patients [58 (age: 33.22 ± 10.23 years old, males/females: 25/33) with and 40 (age: 33.65 ± 10.49 years old, males/females: 14/26) without depressive symptoms] and 54 healthy controls (HCs, age: 32.28 ± 10.56 years old, males/females: 21/33). Patients underwent clinical assessments and resting-state functional MRI (rs-fMRI) at baseline and after 4-week treatment with paroxetine, while HCs underwent rs-fMRI at baseline only. Regional homogeneity (ReHo) was employed to measure intrinsic brain activity. We compared ReHo in patients to HCs and examined changes in ReHo within the patient groups after treatment. Support vector regression (SVR) analyses were conducted separately for each patient group to predict the patients' treatment response.

RESULTS

Both patient groups exhibited higher ReHo in the middle/superior frontal gyrus decreased ReHo in different brain regions compared to HCs. Furthermore, differences in ReHo were detected between the two patient groups. After treatment, the patient groups displayed distinct ReHo change patterns. By utilizing SVR based on baseline abnormal ReHo, we effectively predicted treatment response of patients (p-value for correlation < 0.05).

LIMITATIONS

The dropout rate was relatively high.

CONCLUSIONS

This study identified shared and unique neural substrates in GAD patients with or without depressive symptoms, potentially serving as biomarkers for treatment response prediction. Comorbid depressive symptoms were associated with differences in disease manifestation and treatment response compared to pure GAD cases.

Shared and distinctive dysconnectivity patterns underlying pure generalized anxiety disorder (GAD) and comorbid GAD and depressive symptoms

The resting-state connectivity features underlying pure generalized anxiety disorder (GAD, G1) and comorbid GAD and depressive symptoms (G2) have not been directly compared. Furthermore, it is unclear whether these features might serve as potential prognostic biomarkers and change with treatment. Degree centrality (DC) in G1 (40 subjects), G2 (58 subjects), and healthy controls (HCs, 54 subjects) was compared before treatment, and the DC of G1 or G2 at baseline was compared with that after 4 weeks of paroxetine treatment. Using support vector regression (SVR), voxel-wise DC across the entire brain and abnormal DC at baseline were employed to predict treatment response. At baseline, G1 and G2 exhibited lower DC in the left mid-cingulate cortex and vermis IV/V compared to HCs. Additionally, compared to HCs, G1 had lower DC in the left middle temporal gyrus, while G2 showed higher DC in the right inferior temporal/fusiform gyrus. However, there was no significant difference in DC between G1 and G2. The SVR based on abnormal DC at baseline could successfully predict treatment response in responders in G2 or in G1 and G2. Notably, the predictive performance based on abnormal DC at baseline surpassed that based on DC across the entire brain. After treatment, G2 responders showed lower DC in the right medial orbital frontal gyrus, while no change in DC was identified in G1 responders. The G1 and G2 showed common and distinct dysconnectivity patterns and they could potentially serve as prognostic biomarkers. Furthermore, DC in patients with GAD could change with treatment.

Prediction of anxious depression using multimodal neuroimaging and machine learning

Anxious depression is a common subtype of major depressive disorder (MDD) associated with adverse outcomes and severely impaired social function. It is important to clarify the underlying neurobiology of anxious depression to refine the diagnosis and stratify patients for therapy. Here we explored associations between anxiety and brain structure/function in MDD patients. A total of 260 MDD patients and 127 healthy controls underwent three-dimensional T1-weighted structural scanning and resting-state functional magnetic resonance imaging. Demographic data were collected from all participants. Differences in gray matter volume (GMV), (fractional) amplitude of low-frequency fluctuation ((f)ALFF), regional homogeneity (ReHo), and seed point-based functional connectivity were compared between anxious MDD patients, non-anxious MDD patients, and healthy controls. A random forest model was used to predict anxiety in MDD patients using neuroimaging features. Anxious MDD patients showed significant differences in GMV in the left middle temporal gyrus and ReHo in the right superior parietal gyrus and the left precuneus than HCs. Compared with non-anxious MDD patients, patients with anxious MDD showed significantly different GMV in the left inferior temporal gyrus, left superior temporal gyrus, left superior frontal gyrus (orbital part), and left dorsolateral superior frontal gyrus; fALFF in the left middle temporal gyrus; ReHo in the inferior temporal gyrus and the superior frontal gyrus (orbital part); and functional connectivity between the left superior temporal gyrus(temporal pole) and left medial superior frontal gyrus. A diagnostic predictive random forest model built using imaging features and validated by 10-fold cross-validation distinguished anxious from non-anxious MDD with an AUC of 0.802. Patients with anxious depression exhibit dysregulation of brain regions associated with emotion regulation, cognition, and decision-making, and our diagnostic model paves the way for more accurate, objective clinical diagnosis of anxious depression.