Brain structural network alterations related to serum cortisol levels in drug-naïve, first-episode major depressive disorder patients: a source-based morphometric study

Brain structural changes and molecular analyses in children with benign epilepsy with centrotemporal spikes

BACKGROUND

Benign epilepsy with centrotemporal spikes (BECTS) is a common childhood epilepsy syndrome, accompanied by behavioral problems and cognitive impairments. Previous studies of BECTS-related brain structures applied univariate analysis and showed inconsistent results. And neurotransmitter patterns associated with brain structural alterations were still unclear.

METHODS

Structural images of twenty-one drug-naïve children with BECTS and thirty-five healthy controls (HCs) were scanned. Segmented gray matter volume (GMV) images were decomposed into independent components (ICs) using the source-based morphometry method. Then spatial correlation analyses were applied to examine possible relationships between GMV changes and neurotransmitter systems.

RESULTS

Compared with HCs, drug-naïve children with BECTS showed increased volume in one GMV component (IC7), including bilateral precentral gyrus, bilateral supplementary motor area, left superior frontal cortex, bilateral middle/ inferior frontal cortex and bilateral anterior/ middle cingulate cortex. A positive correlation was observed between one GMV component (IC6) and seizure frequency. There were significantly positive correlations between abnormal GMV in IC7 and serotonergic, GABAergic and glutamatergic systems.

CONCLUSION

These findings provided further evidence of changed GMV in drug-naïve children with BECTS related to their behavioral problems and cognitive impairments, and associated neurotransmitters which could help to better understand neurobiological mechanisms and underlying molecular mechanisms of BECTS.

IMPACT

The article provides further evidence of changed gray matter volume in drug-naïve children with BECTS related to their behavioral problems and cognitive impairments as well as associated neurotransmitters. Most literature to date has applied univariate analysis and showed inconsistent results, and neurotransmitter patterns associated with brain structural alterations were still unclear. Therefore, this article uses multivariate method and JuSpace toolbox to fill the gap. Significantly increased gray matter volume was found in drug-naïve children with BECTS compared with healthy controls. Abnormal gray matter volume was significantly correlated with clinical data and specific neurotransmitters.

The interplay between polygenic score for tumor necrosis factor-α, brain structural connectivity, and processing speed in major depression

Reduced processing speed is a core deficit in major depressive disorder (MDD) and has been linked to altered structural brain network connectivity. Ample evidence highlights the involvement of genetic-immunological processes in MDD and specific depressive symptoms. Here, we extended these findings by examining associations between polygenic scores for tumor necrosis factor-α blood levels (TNF-α PGS), structural brain connectivity, and processing speed in a large sample of MDD patients. Processing speed performance of n = 284 acutely depressed, n = 177 partially and n = 198 fully remitted patients, and n = 743 healthy controls (HC) was estimated based on five neuropsychological tests. Network-based statistic was used to identify a brain network associated with processing speed. We employed general linear models to examine the association between TNF-α PGS and processing speed. We investigated whether network connectivity mediates the association between TNF-α PGS and processing speed. We identified a structural network positively associated with processing speed in the whole sample. We observed a significant negative association between TNF-α PGS and processing speed in acutely depressed patients, whereas no association was found in remitted patients and HC. The mediation analysis revealed that brain connectivity partially mediated the association between TNF-α PGS and processing speed in acute MDD. The present study provides evidence that TNF-α PGS is associated with decreased processing speed exclusively in patients with acute depression. This association was partially mediated by structural brain connectivity. Using multimodal data, the current findings advance our understanding of cognitive dysfunction in MDD and highlight the involvement of genetic-immunological processes in its pathomechanisms.

Gray matter biomarkers for major depressive disorder and manic disorder using logistic regression

The study investigates morphometric changes using surface-based measures and logistic regression in Major depressive-disorder (MDD) and Manic-disorder patients as compared to controls. MDD (n = 21) and manic (n = 20) subjects were recruited from psychiatric clinics, along with 19 healthy-controls from local population, after structured and semi-structured clinical interview (DSM-IV, brief Psychotic-Rating Scale (BPRS), Young Mania Rating Scale (YMRS), Hamilton depression rating scale (HDRS), cognitive function by postgraduate Institute Battery of Brain Dysfunction (PGIBBD)). Using 3D T1-weighted images, gray matter (GM) cortical thickness and GM-based morphometric signatures (using logistic regression) were compared among MDD, manic disorder and controls using analysis of covariance (ANCOVA). No significant difference was found between the MDD and manic disorder patients. When compared to controls, cortical thinning was observed in bilateral rostral middle frontal gyrus and parsopercularis, right lateral occipital cortex, right lingual gyrus in MDD; and bilateral rostral middle frontal and superior frontal gyrus, right middle temporal gyrus, left supramarginal and left precentral gyrus in Manic disorders. Logistic regression analysis exhibited GM cortical thinning in the bilateral parsopercularis, right lateral occipital cortex and lingual gyrus in MDD; and bilateral rostral middle, superior frontal gyri, right middle temporal gyrus in Manic with a sensitivity and specificity of 85.7 % and 94.7 % and 90.0 % and 94.7 %, respectively in comparison with controls. Both groups exhibited GM loss in bilateral rostral middle frontal gyrus brain regions compared to controls. Multivariate analysis revealed common changes in GM in MDD and manic disorders associated with mood temperament, but differences when compared to controls.

Sex differences in cortisol levels in depression: A systematic review and meta-analysis

Higher prevalence of depression in females might be associated with sex-specific cortisol levels. Evidence exists that cortisol levels differ between healthy females and males, however a sex-specific association in depression has not been systematically assessed. Thus, the current study quantifies the existing literature on different cortisol parameters, i.e., basal cortisol, hair cortisol, cortisol awakening response (CAR), and cortisol stress reactivity comparing depressed females and males as well as sex-specific comparisons with healthy controls. Following an extensive literature research, fifty original articles were included. Depressed females had significantly higher hair cortisol, higher CAR, and lower cortisol stress reactivity compared to depressed males. In comparison with sex-matched controls, female patients had significantly higher evening basal cortisol, higher CAR and lower cortisol stress reactivity, and male patients had significantly higher general, morning and evening basal cortisol. Overall, sex as a fundamental driver of cortisol levels in depression needs to be taken into account.

Effect of Tai Chi on Young Adults with Subthreshold Depression via a Stress-Reward Complex: A Randomized Controlled Trial

BACKGROUND

Subthreshold depression is a highly prevalent mood disorder in young adults. Mind-body exercises, such as Tai Chi, have been adopted as interventions for clinical depressive symptoms. However, the possible effect and underlying mechanism of Tai Chi on subthreshold depression of young individuals remain unclear. This randomized controlled study aimed to evaluate the effects of Tai Chi training and tested the combined stress and reward circuitry model for subthreshold depression.

RESULTS

A total of 103 participants completed this trial, with 49 in the 12-week 24-style Tai Chi group and 54 participants in control group. Our results showed significantly lower scores on depressive symptoms (P = 0.002) and anxiety symptoms (P = 0.009) and higher scores on quality of life (P = 0.002) after Tai Chi training. There were significant reductions in salivary cortisol levels (P = 0.007) and putamen gray matter volume (P < 0.001) in the Tai Chi group. The changes in cortisol levels and putamen gray matter volume had direct (bootstrapping confidence interval [- 0.91, - 0.11]) and indirect effects (bootstrapping confidence interval [- 0.65, - 0.19]) on the changes induced by Tai Chi training on depressive symptoms, respectively.

CONCLUSION

The stress-reward complex results indicated an interaction between lowering stress levels and increasing reward circuitry activity associated with the alleviation of depressive symptoms among participants. The 12-week Tai Chi training was effective in improving the symptoms and quality of life of young adults with subthreshold depression. Trial Registration Chinese Registry of Clinical Trials (Registration Number: ChiCTR1900028289, Registered December 12, 2019).

Brain structural abnormalities in adult major depressive disorder revealed by voxel- and source-based morphometry: evidence from the REST-meta-MDD Consortium

BACKGROUND

Neuroimaging studies on major depressive disorder (MDD) have identified an extensive range of brain structural abnormalities, but the exact neural mechanisms associated with MDD remain elusive. Most previous studies were performed with voxel- or surface-based morphometry which were univariate methods without considering spatial information across voxels/vertices.

METHODS

Brain morphology was investigated using voxel-based morphometry (VBM) and source-based morphometry (SBM) in 1082 MDD patients and 990 healthy controls (HCs) from the REST-meta-MDD Consortium. We first examined group differences in regional grey matter (GM) volumes and structural covariance networks between patients and HCs. We then compared first-episode, drug-naïve (FEDN) patients, and recurrent patients. Additionally, we assessed the effects of symptom severity and illness duration on brain alterations.

RESULTS

VBM showed decreased GM volume in various regions in MDD patients including the superior temporal cortex, anterior and middle cingulate cortex, inferior frontal cortex, and precuneus. SBM returned differences only in the prefrontal network. Comparisons between FEDN and recurrent MDD patients showed no significant differences by VBM, but SBM showed greater decreases in prefrontal, basal ganglia, visual, and cerebellar networks in the recurrent group. Moreover, depression severity was associated with volumes in the inferior frontal gyrus and precuneus, as well as the prefrontal network.

CONCLUSIONS

Simultaneous application of VBM and SBM methods revealed brain alterations in MDD patients and specified differences between recurrent and FEDN patients, which tentatively provide an effective multivariate method to identify potential neurobiological markers for depression.

Combined serum IL-6, C-reactive protein, and cortisol may distinguish patients with anhedonia in major depressive disorder

Neuroinflammation and anhedonia in major depressive disorder (MDD) are closely connected, though the exact mechanism is unclear. This study aimed to investigate the relationships between cytokines, C-reactive protein (CRP), cortisol, and anhedonia, revealing the potential predictive value in identifying anhedonic MDD. In total, 66 patients with MDD (29 with anhedonia and 37 without anhedonia) and 66 healthy controls (HCs) were included. The severity of depression and anhedonia was evaluated using the Hamilton Rating Scale for Depression-24 (HAMD-24) and Snaith-Hamilton Pleasure Scale (SHAPS), respectively. Serum cytokines were measured using flow cytofluorometric kits, while CRP and cortisol were measured using enzyme-linked immunosorbent assay kits. We found higher serum levels of interleukin-2 (IL-2), IL-6, and cortisol in MDD than in HC where anhedonic MDD was highest. CRP and IL-6 were positively associated with anhedonia, and cortisol levels were related to both anhedonia and depression. A combination of IL-6, CRP, and cortisol had optimal predictive value for distinguishing anhedonic MDD. Anhedonic MDD has unique neuroendocrine-immune characteristics compared with those without anhedonia. The combination of IL-6, CRP, and cortisol might be an early marker to distinguish anhedonic MDD.

Volume of Amygdala Subregions and Plasma Levels of Brain-Derived Neurotrophic Factor and Cortisol in Patients with s/s Genotype of Serotonin Transporter Gene Polymorphism of First-Episode and Drug-Naive Major Depressive Disorder: An Exploratory Study

The amygdala is a prominent region of the brain that plays a critical role in the pathophysiology of major depressive disorder (MDD). The amygdala is formed from a collection of interconnected substructures (nuclei) that relay signals from multiple brain areas, which suggests that the amygdala has different functions depending on its subregion. There are two main alleles of serotonin transporter gene polymorphism (5-HTTLPR): a 44-bp insertion (l-allele) or deletion (s-allele). The transcriptional activity of the l-allele of the gene is twice that of the s-allele. The present study aimed to investigate the association between the volume of the whole amygdala and subregions of the amygdala in 25 first-episode and drug-naive patients with MDD and 46 healthy controls (HCs) with the s/s genotype of 5-HTTLPR and plasma levels of brain-derived neurotrophic factor (BDNF) or cortisol. No significant difference was observed in the amygdala total and subregion volumes between the HC and MDD groups. No significant difference was found in the plasma levels of BDNF and cortisol between the two groups. In addition, no correlations were found between the total and subregion amygdala volume and plasma levels of cortisol or BDNF.

Volume of Amygdala Subregions and Clinical Manifestations in Patients With First-Episode, Drug-Naïve Major Depression

We examined amygdala subregion volumes in patients with a first episode of major depression (MD) and in healthy subjects. Covariate-adjusted linear regression was performed to compare the MD and healthy groups, and adjustments for age, gender, and total estimated intracranial volume showed no differences in amygdala subregion volumes between the healthy and MD groups. Within the MD group, we examined the association between amygdala subregion volume and the 17-item Hamilton Rating Scale for Depression (HAMD) score and the HAMD subscale score, and found no association in the left amygdala. In the right amygdala, however, there was an inverse linear association between the HAMD total and the HAMD core and lateral nucleus and anterior-amygdaloid-regions. Furthermore, an inverse linear association was seen between the HAMD psychic and the lateral nucleus, anterior-amygdaloid-regions, transition, and whole amygdala. The findings of this study suggest that the severity of MD and some symptoms of MD are associated with right amygdala volume. There have been few reports on the relationship between MD and amygdala subregional volume, and further research is needed to accumulate more data for further validation.

Identifying Subgroups of Major Depressive Disorder Using Brain Structural Covariance Networks and Mapping of Associated Clinical and Cognitive Variables

Background

Identifying data-driven subtypes of major depressive disorder (MDD) holds promise for parsing the heterogeneity of MDD in a neurobiologically informed way. However, limited studies have used brain structural covariance networks (SCNs) for subtyping MDD.

Methods

This study included 145 unmedicated patients with MDD and 206 demographically matched healthy control subjects, who underwent a structural magnetic resonance imaging scan and a comprehensive neurocognitive battery. Patterns of structural covariance were identified using source-based morphometry across both patients with MDD and healthy control subjects. K-means clustering algorithms were applied on dysregulated structural networks in MDD to identify potential MDD subtypes. Finally, clinical and neurocognitive measures were compared between identified subgroups to elucidate the profile of these MDD subtypes.

Results

Source-based morphometry across all individuals identified 28 whole-brain SCNs that encompassed the prefrontal, anterior cingulate, and orbitofrontal cortices; basal ganglia; and cerebellar, visual, and motor regions. Compared with healthy control subjects, individuals with MDD showed lower structural network integrity in three networks including default mode, ventromedial prefrontal cortical, and salience networks. Clustering analysis revealed two MDD subtypes based on the patterns of structural network abnormalities in these three networks. Further profiling revealed that patients in subtype 1 had younger age of onset and more symptom severity as well as greater deficits in cognitive performance than patients in subtype 2.

Conclusions

Overall, we identified two MDD subtypes based on SCNs that differed in their clinical and cognitive profile. Our results represent a proof-of-concept framework for leveraging these large-scale SCNs to parse heterogeneity in MDD.