White Matter Network Disruption Is Associated With Melancholic Features in Major Depressive Disorder

Investigating Mood and Cognition in People with Multiple Sclerosis: A Prospective Study Protocol

Multiple sclerosis (MS) is an immune-mediated neurological disorder that affects one million people in the United States. Up to 50% of people with MS experience depression, yet the mechanisms of depression in MS remain under-investigated. Studies of medically healthy participants with depression have described associations between white matter variability and depressive symptoms, but frequently exclude participants with medical comorbidities and thus cannot be extrapolated to people with intracranial diseases. White matter lesions are a key pathologic feature of MS and could disrupt pathways involved in depression symptoms. The purpose of this study is to investigate the impact of brain network disruption on depression using MS as a model. We will obtain structured clinical and cognitive assessments from two hundred fifty participants with MS and prospectively evaluate white matter lesion burden as a predictor of depressive symptoms. Ethics approval was obtained from The University of Pennsylvania Institutional Review Board (Protocol #853883). The results of this study will be presented at scientific meetings and conferences and published in peer-reviewed journals.

Multimodal abnormalities of brain structures in adolescents and young adults with major depressive disorder: An activation likelihood estimation meta-analysis

BACKGROUND

Major depressive disorder (MDD) in adolescents and young adults contributes significantly to global morbidity, with inconsistent findings on brain structural changes from structural magnetic resonance imaging studies. Activation likelihood estimation (ALE) offers a method to synthesize these diverse findings and identify consistent brain anomalies.

AIM

To identify consistent brain structural changes in adolescents and young adults with MDD using ALE meta-analysis.

METHODS

We performed a comprehensive literature search in PubMed, Web of Science, Embase, and Chinese National Knowledge Infrastructure databases for neuroimaging studies on MDD among adolescents and young adults published up to November 19, 2023. Two independent researchers performed the study selection, quality assessment, and data extraction. The ALE technique was employed to synthesize findings on localized brain function anomalies in MDD patients, which was supplemented by sensitivity analyses.

RESULTS

Twenty-two studies comprising fourteen diffusion tensor imaging (DTI) studies and eight voxel-based morphometry (VBM) studies, and involving 451 MDD patients and 465 healthy controls (HCs) for DTI and 664 MDD patients and 946 HCs for VBM, were included. DTI-based ALE demonstrated significant reductions in fractional anisotropy (FA) values in the right caudate head, right insula, and right lentiform nucleus putamen in adolescents and young adults with MDD compared to HCs, with no regions exhibiting increased FA values. VBM-based ALE did not demonstrate significant alterations in gray matter volume. Sensitivity analyses highlighted consistent findings in the right caudate head (11 of 14 analyses), right insula (10 of 14 analyses), and right lentiform nucleus putamen (11 of 14 analyses).

CONCLUSION

Structural alterations in the right caudate head, right insula, and right lentiform nucleus putamen in young MDD patients may contribute to its recurrent nature, offering insights for targeted therapies.

Reduced gray matter volume of the hippocampal tail in melancholic depression: evidence from an MRI study

BACKGROUND

Melancholic depression (MD) is one of the most prevalent and severe subtypes of major depressive disorder (MDD). Previous studies have revealed inconsistent results regarding alterations in grey matter volume (GMV) of the hippocampus and amygdala of MD patients, possibly due to overlooking the complexity of their internal structure. The hippocampus and amygdala consist of multiple and functionally distinct subregions, and these subregions may play different roles in MD. This study aims to investigate the volumetric alterations of each subregion of the hippocampus and amygdala in patients with MD and non-melancholic depression (NMD).

METHODS

A total of 146 drug-naïve, first-episode MDD patients (72 with MD and 74 with NMD) and 81 gender-, age-, and education-matched healthy controls (HCs) were included in the study. All participants underwent magnetic resonance imaging (MRI) scans. The subregional segmentation of hippocampus and amygdala was performed using the FreeSurfer 6.0 software. The multivariate analysis of covariance (MANCOVA) was used to detect GMV differences of the hippocampal and amygdala subregions between three groups. Partial correlation analysis was conducted to explore the relationship between hippocampus or amygdala subfields and clinical characteristics in the MD group. Age, gender, years of education and intracranial volume (ICV) were included as covariates in both MANCOVA and partial correlation analyses.

RESULTS

Patients with MD exhibited a significantly lower GMV of the right hippocampal tail compared to HCs, which was uncorrelated with clinical characteristics of MD. No significant differences were observed among the three groups in overall and subregional GMV of amygdala.

CONCLUSIONS

Our findings suggest that specific hippocampal subregions in MD patients are more susceptible to volumetric alterations than the entire hippocampus. The reduced right hippocampal tail may underlie the unique neuropathology of MD. Future longitudinal studies are required to better investigate the associations between reduced right hippocampal tail and the onset and progression of MD.

White matter-based brain network topological properties associated with individual impulsivity

Delay discounting (DD), a parameter derived from the intertemporal choice task, is a representative behavioral indicator of choice impulsivity. Previous research reported not only an association between DD and impulsive control disorders and negative health outcomes but also the neural correlates of DD. However, to date, there are few studies investigating the structural brain network topologies associated with individual differences in DD and whether self-reported measures (BIS-11) of impulsivity associated with DD share the same or distinct neural mechanisms is still unclear. To address these issues, here, we combined graph theoretical analysis with diffusion tensor imaging to investigate the associations between DD and the topological properties of the structural connectivity network and BIS-11 scores. Results revealed that people with a steep DD (greater impatience) had decreased small-worldness (a shift toward weaker small-worldnization) and increased degree centrality in the medial superior prefrontal cortex, associated with subjective value in the task. Though DD was associated with the BIS-11 motor impulsiveness subscale, this subscale was linked to topological properties different from DD; that is, high motor impulsiveness was associated with decreased local efficiency (less segregation) and decreased degree centrality in the precentral gyrus, involved in motor control. These findings provide insights into the systemic brain characteristics underlying individual differences in impulsivity and potential neural markers which could predict susceptibility to impulsive behaviors.

Altered White Matter Network Topology in Panic Disorder

Panic disorder (PD) is an anxiety disorder that impairs life quality and social function and is associated with distributed brain regions. However, the alteration of the structural network remains unclear in PD patients. This study explored the specific characteristics of the structural brain network in patients with PD by graph theory analysis of diffusion tensor images (DTI). A total of 81 PD patients and 48 matched healthy controls were recruited for this study. The structural networks were constructed, and the network topological properties for individuals were estimated. At the global level, the network efficiency was higher, while the shortest path length and clustering coefficient were lower in the PD group compared to the healthy control (HC) group. At the nodal level, the PD group showed a widespread higher nodal efficiency and lower average shortest path length in the prefrontal, sensorimotor, limbic, insula, and cerebellum regions. Overall, the current results showed that the alteration of information processing in the fear network might play a role in the pathophysiology of PD.