Superior temporal gyrus and cerebellar loops predict nonsuicidal self-injury in major depressive disorder patients by multimodal neuroimaging

Graph convolutional network with attention mechanism improve major depressive depression diagnosis based on plasma biomarkers and neuroimaging data

BACKGROUND

The absence of clinically-validated biomarkers or objective protocols hinders effective major depressive disorder (MDD) diagnosis. Compared to healthy control (HC), MDD exhibits anomalies in plasma protein levels and neuroimaging presentations. Despite extensive machine learning studies in psychiatric diagnosis, a reliable tool integrating multi-modality data is still lacking.

METHODS

In this study, blood samples from 100 MDD and 100 HC were analyzed, along with MRI images from 46 MDD and 49 HC. Here, we devised a novel algorithm, integrating graph neural networks and attention modules, for MDD diagnosis based on inflammatory cytokines, neurotrophic factors, and Orexin A levels in the blood samples. Model performance was assessed via accuracy and F1 value in 3-fold cross-validation, comparing with 9 traditional algorithms. We then applied our algorithm to a dataset containing both the aforementioned protein quantifications and neuroimages, evaluating if integrating neuroimages into the model improves performance.

RESULTS

Compared to HC, MDD showed significant alterations in plasma protein levels and gray matter volume revealed by MRI. Our new algorithm exhibited superior performance, achieving an F1 value and accuracy of 0.9436 and 94.08 %, respectively. Integration of neuroimaging data enhanced our novel algorithm's performance, resulting in an improved F1 value and accuracy, reaching 0.9543 and 95.06 %.

LIMITATIONS

This single-center study with a small sample size requires future evaluations on a larger test set for improved reliability.

CONCLUSIONS

In comparison to traditional machine learning models, our newly developed MDD diagnostic model exhibited superior performance and showed promising potential for inclusion in routine clinical diagnosis for MDD.

The effects of childhood trauma on nonsuicidal self-injury and depressive severity among adolescents with major depressive disorder: The different mediating roles of positive and negative coping styles

OBJECTIVE

We aimed to examine whether positive and negative coping styles mediated the influences of childhood trauma on NSSI or depressive severity in adolescents with major depressive disorder (MDD).

METHODS

The Children's Depression Inventory (CDI), the Ottawa Self-Injury Inventory Chinese Revised Edition (OSIC), the short-form Childhood Trauma Questionnaire (CTQ-SF), and the Simplified Coping Style Questionnaire (SCSQ) were evaluated in 313 adolescents with MDD.

RESULTS

MDD adolescents with NSSI had higher CTQ-SF total score, emotional and sexual abuse subscale scores, but lower CDI total and subscale scores compared to the patients without NSSI. The multiple linear regression analysis revealed that emotional abuse (β = 0.075, 95 % CI: 0.042-0.107) and ineffectiveness (β = -0.084, 95 % CI: -0.160 ∼ -0.009) were significantly associated with the frequency of NSSI in adolescents with MDD, but emotional abuse (β = 0.884, 95 % CI: 0.570-1.197), sexual abuse (β = 0.825, 95 % CI: 0.527-1.124) and negative coping style (β = 0.370, 95 % CI: 0.036-0.704) were independently associated with the depressive severity in these adolescents. Furthermore, the mediation analysis demonstrated that positive coping style partially mediates the effect of childhood trauma on NSSI (Indirect effect = 0.002, 95 % bootCI: 0.001-0.004), while the negative coping style partially mediates the relationship between childhood trauma and depressive severity (Indirect effect = 0.024, 95 % bootCI: 0.005-0.051) in adolescents with MDD.

LIMITATIONS

A cross-sectional design, the retrospective self-reported data, the small sample size.

CONCLUSION

Our findings suggest that coping styles may serve as mediators on the path from childhood trauma to NSSI or depressive severity in MDD adolescents.

Integrative molecular and structural neuroimaging analyses of the interaction between depression and age of onset: A multimodal magnetic resonance imaging study

Depression is a neurodevelopmental disorder that exhibits progressive gray matter volume (GMV) atrophy. Research indicates that brain development is influential in depression-induced GMV alterations. However, the interaction between depression and age of onset is not well understood by the underlying molecular and neuropathological mechanisms. Thus, 152 first-episode depression individuals and matched 130 healthy controls (HCs) were recruited to undergo T1-weighted high-resolution magnetic resonance imaging for this study. By two-way ANOVA, age and diagnosis were used as factors when analyzing the interaction of GMV in the participants. Then, spatial correlations between neurotransmitter maps and factor-related volume maps are established. Results illustrate a pronounced antagonistic interaction between depression and age of onset in the right insula, superior temporal gyrus, anterior cingulate gyrus, and orbitofrontal gyrus. Depression-caused reductions in GMV are mainly distributed in thalamic-limbic-cortical regions, regardless of age. For the main effect of age, adults exhibit brain atrophy in frontal, cerebellum, parietal, and temporal lobe structures. Cross-modal correlations showed that GMV changes in the interactive regions were linked with the serotonergic system and dopaminergic systems. Summarily, our results reveal the interaction between depression and age of onset in neurobiological mechanisms, which provide hints for future treatment of different ages of depression.

Pathway from childhood trauma to nonsuicidal self-injury in adolescents with major depressive disorder: the chain-mediated role of psychological resilience and depressive severity

This study aimed to explore the pathway from childhood trauma to nonsuicidal self-injury (NSSI) in adolescents with major depressive disorder (MDD) and to examine the chain-mediating role of psychological resilience and depressive symptoms in this pathway. A total of 391 adolescents with MDD were recruited in the present study. The Chinese version of the Childhood Trauma Questionnaire-Short Form (CTQ-SF), the Chinese version of the Symptoms Check List-90 (SCL-90), the Chinese version of the Conner-Davidson Resilience Scale (CD-RISC), and the Ottawa Self-Injury Inventory Chinese Revised Edition (OSIC) were used to evaluate childhood trauma, depressive symptoms, psychological resilience and NSSI, respectively. Our results showed that 60.87% of adolescents with MDD had NSSI in the past month. Childhood trauma frequency was negatively correlated with psychological resilience but positively correlated with depressive symptoms and NSSI severity in adolescents with MDD. The stepwise logistic regression analysis identified that age, childhood trauma and depressive symptoms could independently predict the occurrence of NSSI, and the three-step hierarchical regression showed that childhood trauma, psychological resilience and depressive symptoms were all significantly associated with NSSI frequency in adolescents with MDD. Furthermore, the chain-mediation analysis revealed that psychological resilience and depression serially mediated the relationship between childhood trauma and NSSI in adolescents with MDD. Interventions targeted at improving resilience and depression may mitigate the impact of childhood trauma severity on NSSI risk in adolescents with MDD.

Managing Cancer and Living Meaningfully (CALM) alleviates chemotherapy related cognitive impairment (CRCI) in breast cancer survivors: A pilot study based on resting-state fMRI

BACKGROUND

Chemotherapy related cognitive impairment (CRCI) is a type of memory and cognitive impairment induced by chemotherapy and has become a growing clinical problem. Breast cancer survivors (BCs) refer to patients from the moment of breast cancer diagnosis to the end of their lives. Managing Cancer and Living Meaningfully (CALM) is a convenient and easy-to-apply psychological intervention that has been proven to improve quality of life and alleviate CRCI in BCs. However, the underlying neurobiological mechanisms remain unclear. Resting-state functional magnetic resonance imaging (rs-fMRI) has become an effective method for understanding the neurobiological mechanisms of brain networks in CRCI. The fractional amplitude of low-frequency fluctuations (fALFF) and ALFF have often been used in analyzing the power and intensity of spontaneous regional resting state neural activity.

METHODS

The recruited BCs were randomly divided into the CALM group and the care as usual (CAU) group. All BCs were evaluated by the Functional Assessment of Cancer Therapy Cognitive Function (FACT-Cog) before and after CALM or CAU. The rs-fMRI imaging was acquired before and after CALM intervention in CALM group BCs. The BCs were defined as before CALM intervention (BCI) group and after CALM intervention (ACI) group.

RESULTS

There were 32 BCs in CALM group and 35 BCs in CAU group completed the overall study. There were significant differences between the BCI group and the ACI group in the FACT-Cog-PCI scores. Compared with the BCI group, the ACI group showed lower fALFF signal in the left medial frontal gyrus and right sub-gyral and higher fALFF in the left occipital_sup and middle occipital gyrus. There was a significant positive correlation between hippocampal ALFF value and FACT-Cog-PCI scores.

CONCLUSIONS

CALM intervention may have an effective function in alleviating CRCI of BCs. The altered local synchronization and regional brain activity may be correlated with the improved cognitive function of BCs who received the CALM intervention. The ALFF value of hippocampus seems to be an important factor in reflect cognitive function in BCs with CRCI and the neural network mechanism of CALM intervention deserves further exploration to promote its application.