Journal of affective disorders最新文献

Background: Scarce research has investigated associations between suicidal ideation and the gut microbiota. We aimed to explore variations in the gut microbiome associated with suicidal ideation and major depressive disorder (MDD).

Method: A case-control study compared abundances of fecal microbiota and biomarkers of gut permeability among patients with MDD, with or without suicidal ideation, and healthy volunteers without depression. Information on demographic variables and assessments of suicidal ideation (Beck Suicidal Ideation Scale), depression (Hamilton Depression Scale, Patient Health Questionnaire, Hospital Anxiety and Depression Scale- Depression), as well as anxiety (Hospital Anxiety and Depression Scale- Anxiety), were obtained. Univariate and multivariate regression model was performed to explore the possible predictors of suicidal ideation.

Results: Among the 140 participants, significant differences in Beta diversity were found between MDD patients with (n = 43) or without suicidal ideation (n = 34), and healthy volunteers (n = 42) (all p < 0.001). The strain of g-Phascolarctobacterium was found to have significant positive associations with scores of BSSI and BSSI Part 1 (suicidal ideation), particularly in MDD patients with suicidal ideation, after controlling for demographic and mood covariates. Mediation analyses revealed that g-Phascolarctobacterium may be a partial mediator between depression and suicidal ideation; however, it is also possible that the association between g-Phascolarctobacterium and suicidal ideation was partially mediated by the level of depression.

Conclusion: We found different compositions, diversities, and possible mediating of the gut microbiome associated with suicidal ideations. Potential mechanisms need further investigation to establish whether this reflects a biological process that might be the focus for intervention development.

Synopsis: Our objective was to investigate whether the diversities and abundances of the gut microbiome varied in people with or without suicidal ideation and with or without MDD after considering possible demographic and mood confounders.

Background: Although theory and research implicate self-criticism as a risk factor for non-suicidal self-injury (NSSI), the nature of this association in daily life remains unclear. This study used ecological momentary assessment (EMA) to address whether (1) trait and state self-criticism elevate the risk of NSSI, (2) state self-criticism predicts NSSI behavior in real-time via increased NSSI urge intensity, and (3) the risk pattern extends to disordered eating (DE; binge eating, purging, restrictive eating).

Methods: A total of 125 treatment-seeking individuals who self-injure (87.20 % female; M_age = 22.98, SD = 5.32) completed measures of trait self-criticism at intake, followed by six daily assessments for 28 days (15,098 assessments; median compliance = 78.6 %) measuring self-critical thoughts, NSSI, and DE. Multilevel vector autoregressive models were constructed within a dynamic structural equation modeling framework.

Results: Patients who reported higher mean state self-critical thoughts experienced more intense NSSI urges and an increased risk for NSSI behavior during treatment. Higher-than-usual self-critical thoughts predicted NSSI urge intensity and NSSI behavior within the following 2 h. NSSI urge intensity partially mediated the effect of self-critical thoughts on NSSI behavior. Trait self-criticism did not predict comorbid DE, but aggregated state self-critical thoughts were associated with binge and restrictive eating. The within-person risk pattern of self-criticism generally extended to DE, with full mediation via DE urges for purging and restrictive eating, but not binge eating.

Conclusions: Self-criticism is a real-time predictor of NSSI and comorbid DE. These findings underscore the relevance of monitoring self-criticism outside the therapy room, as it may be an important treatment target.

Introduction: Osteoporosis, a significant public health concern, affects millions of adult women globally, leading to increased morbidity and fracture risk. Antidepressant use, prevalent in this demographic, is suggested to influence bone mineral density (BMD), yet evidence remains limited across antidepressant classes.

Objective/aim: We investigated the association between antidepressant use and osteoporosis in a representative sample of adult women in the United States, focusing on different classes of antidepressants and their potential associations with BMD and fracture risk.

Methods: We conducted a cross-sectional analysis using data from ten cohorts of the National Health and Nutrition Examination Survey (NHANES) spanning 1999-2000 to 2017-2020. The sample included adult women, with data collected on antidepressant use, BMD scores, and reported fractures. Statistical models adjusted for potential confounders such as Major Depressive Disorder (MDD), age, physical activity, and comorbidities.

Results: Antidepressant use was associated with a 44 % increase in the odds of osteoporosis. Phenylpiperazines showed the highest association, followed by miscellaneous antidepressants and tricyclic antidepressants (TCAs). Selective serotonin reuptake inhibitors (SSRIs) and serotonin-norepinephrine reuptake inhibitors (SNRIs) also demonstrated significant, though comparatively lower associations. The odds of fractures were elevated by 62 % among antidepressant users, particularly with phenylpiperazines and miscellaneous antidepressants. A dose-response analysis indicated that both the number and duration of antidepressants were associated with increased odds of osteoporosis.

Conclusion: Our findings underscore the need for heightened awareness of the adverse effects of antidepressants on bone health, particularly in adult women. Careful consideration is necessary when prescribing these medications, especially in populations at risk for osteoporosis and MDD.

Background: Recent researches have reported that frequency-specific patterns of neural activity contain not only rhythmically sustained oscillations but also transient-bursts of isolated events. The aim of this study was to investigated the correlation between beta burst and depression in order to explore depressive disease and the neurological underpinnings of disease-related symptoms.

Methods: We collected resting-state MEG recordings from 30 depressive patients and a matched 40 healthy controls. A Hidden Markov Model (HMM) was applied on source-space time courses for 78 cortical regions of the AAL atlas and the temporal characteristics of beta burst from the matched HMM states were captured. Group differences were evaluated on these beta burst characteristics after permutation tests and, for the depressive group, associations between burst characteristics and clinical symptom severity were determined using Spearman correlation coefficients.

Results: At a threshold of p=0.05corrected, burst characteristics revealed significant differences between depression patients and controls at the group level, including increased burst amplitude in frontal lobe, decreased burst duration in occipital regions, increased burst rate and decreased burst interval time in some brain regions. Furthermore, burst amplitude in the orbitofrontal cortex (OFC) was positively related to the severity of sleep disturbance and burst rate in the OFC was negatively related to the severity of anxiety in depression patients.

Conclusions: The findings highlight OFC may be a targeted area responsible for the anxiety and sleep disturbance symptom by abnormal beta burst in depressive patients and beta burst characteristics of OFC might serve as a neuro-marker for the depression.