Unbalanced amygdala communication in major depressive disorder

Polygenic overlap between subjective well-being and psychiatric disorders and cross-ancestry validation

Subjective well-being (SWB) is important for understanding human behaviour and health. Although the connection between SWB and psychiatric disorders has been studied, common genetic mechanisms remain unclear. This study aimed to explore the genetic relationship between SWB and psychiatric disorders. Bivariate causal mixture modelling (MiXeR), polygenic risk score (PRS) and Mendelian randomization (MR) analyses showed substantial polygenic overlap and associations between SWB and the psychiatric disorders. Subsequent replication studies in East Asian populations confirmed the polygenic overlap between schizophrenia and SWB. The conditional and conjunctional false discovery rate analyses identified additional or shared genetic loci associated with SWB or psychiatric disorders. Functional annotation revealed enrichment of specific brain tissues and genes associated with SWB. The identified genetic loci showed cross-ancestry transferability between the European and Korean populations. Our findings provide valuable insights into the common genetic mechanisms underlying SWB and psychiatric disorders.

Alterations in orbitofrontal cortex communication relate to suicidal attempts in patients with major depressive disorder

BACKGROUND

Investigating how the interaction between the orbitofrontal cortex (OFC) and various brain regions/functional networks in major depressive disorder (MDD) patients with a history of suicide attempt (SA) holds importance for understanding the neurobiology of this population.

METHODS

We employed resting-state functional magnetic resonance imaging (rs-fMRI) to analyze the OFC's functional segregation in 586 healthy individuals. A network analysis framework was then applied to rs-fMRI data from 86 MDD-SA patients and 85 MDD-Control patients, utilizing seed mappings of OFC subregions and a multi-connectivity-indicator strategy involving cross-correlation, total interdependencies, Granger causality, and machine learning.

RESULTS

Four functional subregions of left and right OFC, were designated as seed regions of interest. Relative to the MDD-Control group, the MDD-SA group exhibited enhanced functional connectivity (FC) and attenuated interaction between the OFC and the sensorimotor network, imbalanced communication between the OFC and the default mode network, enhanced FC and interaction between the OFC and the ventral attention network, enhanced interaction between the OFC and the salience network, and attenuated FC between the OFC and the frontoparietal network.

LIMITATIONS

The medication and treatment condition of patients with MDD was not controlled, so the medication effect on the alteration model cannot be affirmed.

CONCLUSION

The findings suggest an imbalanced interaction pattern between the OFC subregions and a set of cognition- and emotion-related functional networks/regions in the MDD-SA group.

Disrupted basolateral amygdala circuits supports negative valence bias in depressive states

Negative bias is an essential characteristic of depressive episodes leading patients to attribute more negative valence to environmental cues. This negative bias affects all levels of information processing including emotional response, attention and memory, leading to the development and maintenance of depressive symptoms. In this context, pleasant stimuli become less attractive and unpleasant ones more aversive, yet the related neural circuits underlying this bias remain largely unknown. By studying a mice model for depression chronically receiving corticosterone (CORT), we showed a negative bias in valence attribution to olfactory stimuli that responds to antidepressant drug. This result paralleled the alterations in odor value assignment we observed in bipolar depressed patients. Given the crucial role of amygdala in valence coding and its strong link with depression, we hypothesized that basolateral amygdala (BLA) circuits alterations might support negative shift associated with depressive states. Contrary to humans, where limits in spatial resolution of imaging tools impair easy amygdala segmentation, recently unravelled specific BLA circuits implicated in negative and positive valence attribution could be studied in mice. Combining CTB and rabies-based tracing with ex vivo measurements of neuronal activity, we demonstrated that negative valence bias is supported by disrupted activity of specific BLA circuits during depressive states. Chronic CORT administration induced decreased recruitment of BLA-to-NAc neurons preferentially involved in positive valence encoding, while increasing recruitment of BLA-to-CeA neurons preferentially involved in negative valence encoding. Importantly, this dysfunction was dampened by chemogenetic hyperactivation of BLA-to-NAc neurons. Moreover, altered BLA activity correlated with durable presynaptic connectivity changes coming from the paraventricular nucleus of the thalamus, recently demonstrated as orchestrating valence assignment in the amygdala. Together, our findings suggest that specific BLA circuits alterations might support negative bias in depressive states and provide new avenues for translational research to understand the mechanisms underlying depression and treatment efficacy.

Transcriptional patterns of amygdala functional connectivity in first-episode, drug-naïve major depressive disorder

Previous research has established associations between amygdala functional connectivity abnormalities and major depressive disorder (MDD). However, inconsistencies persist due to limited sample sizes and poorly elucidated transcriptional patterns. In this study, we aimed to address these gaps by analyzing a multicenter magnetic resonance imaging (MRI) dataset consisting of 210 first-episode, drug-naïve MDD patients and 363 age- and sex-matched healthy controls (HC). Using Pearson correlation analysis, we established individualized amygdala functional connectivity patterns based on the Automated Anatomical Labeling (AAL) atlas. Subsequently, machine learning techniques were employed to evaluate the diagnostic utility of amygdala functional connectivity for identifying MDD at the individual level. Additionally, we investigated the spatial correlation between MDD-related amygdala functional connectivity alterations and gene expression through Pearson correlation analysis. Our findings revealed reduced functional connectivity between the amygdala and specific brain regions, such as frontal, orbital, and temporal regions, in MDD patients compared to HC. Importantly, amygdala functional connectivity exhibited robust discriminatory capability for characterizing MDD at the individual level. Furthermore, we observed spatial correlations between MDD-related amygdala functional connectivity alterations and genes enriched for metal ion transport and modulation of chemical synaptic transmission. These results underscore the significance of amygdala functional connectivity alterations in MDD and suggest potential neurobiological mechanisms and markers for these alterations.

Characterizing Major Depressive Disorder (MDD) using alpha-band activity in resting-state electroencephalogram (EEG) combined with MATRICS Consensus Cognitive Battery (MCCB)

BACKGROUND

The diagnosis of major depressive disorder (MDD) is commonly based on the subjective evaluation by experienced psychiatrists using clinical scales. Hence, it is particularly important to find more objective biomarkers to aid in diagnosis and further treatment. Alpha-band activity (7-13 Hz) is the most prominent component in resting electroencephalogram (EEG), which is also thought to be a potential biomarker. Recent studies have shown the existence of multiple sub-oscillations within the alpha band, with distinct neural underpinnings. However, the specific contribution of these alpha sub-oscillations to the diagnosis and treatment of MDD remains unclear.

METHODS

In this study, we recorded the resting-state EEG from MDD and HC populations in both open and closed-eye state conditions. We also assessed cognitive processing using the MATRICS Consensus Cognitive Battery (MCCB).

RESULTS

We found that the MDD group showed significantly higher power in the high alpha range (10.5-11.5 Hz) and lower power in the low alpha range (7-8.5 Hz) compared to the HC group. Notably, high alpha power in the MDD group is negatively correlated with working memory performance in MCCB, whereas no such correlation was found in the HC group. Furthermore, using five established classification algorithms, we discovered that combining alpha oscillations with MCCB scores as features yielded the highest classification accuracy compared to using EEG or MCCB scores alone.

CONCLUSIONS

Our results demonstrate the potential of sub-oscillations within the alpha frequency band as a potential distinct biomarker. When combined with psychological scales, they may provide guidance relevant for the diagnosis and treatment of MDD.

Correlation of event-related potentials N170 with dysfunctional attitudes in patients with major depressive disorder

BACKGROUND

Cognitive impairment frequently accompanies first-episode major depressive disorder (MDD) in patients. Early detection and intervention for cognitive impairment can enhance the quality of life for individuals with depressive disorders. Impaired emotion recognition may serve as an initial manifestation of cognitive impairment in these patients. This study examines the characteristics of event-related potentials N170 and dysfunctional attitudinal questionnaire total scores, as well as each factor and their correlation, revealing characteristic electroencephalogram (EEG) changes associated with cognitive impairment in first-episode MDD patients.

METHOD

A total of 88 patients experiencing first-episode MDD and 29 healthy volunteers from the same period participated in the study. They underwent event-related potential N170 measures to assess mood recognition function, the 17-item Hamilton depression scale (HAMD-17) to evaluate the severity of depressive disorder, and the Dysfunctional Attitudes Scales(DAS) to appraise cognitive function.

RESULT

The dysfunctional attitude questionnaire's total score and each factor score were higher in the MDD group compared to the healthy control (HC) group. The MDD group exhibited lower amplitudes than the HC group at CZ, PZ, POZ, P7, PO7, P8, and PO8 electrode points. A correlation was identified between the P7 and PO7 electrode points of the event-related potential N170 and cognitive function.

LIMITATION

This study solely considered neutral face emotional stimuli and did not account for depressive disorder subtypes.

CONCLUSION

Differences were observed between the MDD and HC groups in cognitive function and N170 amplitude in the central brain region (CZ, PZ, POZ), left posterior temporal region (P7), left occipitotemporal region (PO7), right posterior temporal region (P8), and right occipitotemporal region (PO8). Additionally, a correlation was found between N170 latency in the left posterior temporal region of the brain (P7) and the left occipitotemporal region (PO7) with cognitive function.