Depression and Anxiety最新文献

Background: Previous studies have documented brain structural changes in major depressive disorder with suicidal ideation (MDDSI). While sex differences in brain structure have been observed in MDD, the specific differences in MDDSI remain underexplored. This study aims to examine sex-specific cortical structural changes in MDDSI patients, with the goal of improving suicide risk assessment and supporting the development of sex-specific interventions.

Methods: High-resolution T1-weighted magnetic resonance imaging (MRI) data were acquired from 177 participants, including 117 patients with MDD (44 males and 73 females) and 60 healthy controls (HC; 23 males and 37 females). Using FreeSurfer, we assessed the main effects of both group and sex, as well as sex-by-group interactions, on cortical thickness (CT), surface area (SA), cortical volume (CV), and local gyrification index (LGI). Pearson partial correlation analysis was performed to examine the associations between sex-specific regions and SI scores.

Results: Patients with MDDSI exhibited significantly reduced LGI in the right inferior and superior parietal cortices, irrespective of sex. Significant sex-by-group interactions were identified and post hoc analyses revealed that male MDDSI patients showed significantly greater CT in the right lingual gyrus (LG) compared to their female counterparts, along with smaller SA in the right lateral occipital cortex (LOC) and reduced CV in the right pericalcarine cortex (PCAL) compared to their sex-matched MDD patients without SI (MDDNonSI). No significant associations were found between these structural changes and SI scores.

Conclusion: This study highlights sex-specific differences in cortical structures in MDDSI patients. These findings contribute to understanding the neurobiological mechanisms underlying MDD with SI.

Trial Registration: Chinese Clinical Trial Registry (ChiCTR): ChiCTR2100049646

Background: Depression and anxiety are among the most common mental health issues of older populations, and as such they are frequently monitored covariates. The possibilities for collecting research data has grown with the recent emergence of user-friendly online survey platforms. However, to what extent the populations of older persons who participate in such research are similar to the general population remains unclear. We investigated the affective health of an open online sample of older adults (65+) in contrast to a representative randomised in-person interview sample.

Methods: The surveys were conducted in 2021 during the COVID-19 pandemic in the Czech Republic after the second wave of anti-COVID-19 vaccination. The online sample (N = 389) was recruited via the Internet. Participants of the in-person study (N = 633) were randomly approached according to quotas for representativeness. The administered questionnaires included a health status self-report, the Geriatric Depression Scale (GDS) and the Geriatric Anxiety Inventory – Short form (GAI-SF).

Results: Online participants reported better mental and general health; that is, they reported fewer depressive and anxiety symptoms than the randomised representative sample. In both samples, women showed higher levels of anxiety than men. Subjective general health was associated with mental health. In the randomised representative sample, in contrast to the online sample, the level of depression increased significantly with age. The open non-randomised calls for participants attracted a higher percentage of women and people with higher education than are in the general older population.

Conclusions: Older research volunteers recruited online can be expected to be subjectively healthier and to differ largely from the general population in their sociodemographic characteristics.

Background: Major depressive disorder (MDD) is a psychiatric disorder characterized by alterations in global signal (GS) topography across various neural networks and brain regions, including the default mode network and sensorimotor-related areas. While previous research has demonstrated the potential of global brain activity measures to differentiate MDD from healthy controls (HCs), specific changes in GS distribution among MDD patients with and without anxiety remain poorly understood. This study aims to investigate anxiety-related alterations in GS topography in MDD and their associations with clinical symptoms.

Methods: Resting-state functional magnetic resonance imaging (fMRI) and T1-weighted imaging data were collected from 334 MDD patients with anxiety, 145 MDD patients without anxiety, and 307 HCs as part of the REST-meta-MDD consortium. We computed GS topography using GS correlation (GSCORR) and assessed structural–functional interaction (SFI) by examining the relationship between gray matter volume and GS for each subject.

Results: Our analysis revealed no significant differences in GS topography among the three groups at either the whole-brain or network levels. However, decreased GSCORR was observed in the right precentral gyrus, insula, and posterior parieto-occipital cortex in anxious MDD patients compared to HC. SFI analyses indicated anxiety-related alterations in the sensorimotor network, precuneus, putamen, and middle temporal gyrus. Moreover, GSCORR in the inferior parietal lobe and cerebellum exhibited specific correlation trends with anxiety and depression symptoms, respectively.

Conclusions: These findings underscore an abnormal topographic shift in global brain activity in MDD patients with anxiety, offering a new insight into understanding brain dysfunction associated with this disorder.

Background: The association between ambient air pollution and the onset of depression and anxiety has attracted significant scholarly interest; however, its underlying mechanisms remain elusive.

Objective: The primary objective of this study is to assess the connection between air pollution and the onset of depression and anxiety, with a specific emphasis on uncovering the potential pathways influenced by high-dimensional proteomic markers.

Design, setting, and participants: This prospective, nationwide population-based cohort study utilized data from the UK Biobank, incorporating an analysis of proteomic data from 38,301 participants.

Method: Air pollution levels for particulate matter (PM) diameters of ≤2.5 μm (PM_2.5), ≤10 μm (PM₁₀), 2.5–10 μm (PM_coarse), nitrogen oxides (NO_x), and nitrogen dioxide (NO₂) were estimated in 2010. The depression and anxiety symptoms were assessed through self-report questionnaires at baseline and at the 7-year follow-up, and diagnoses were determined using ICD-9/10 codes from hospital records. Plasma proteomic data for 1463 proteins was measured using the Olink platform. A two-step regression approach was used to identify proteins associated with both air pollution and depression/anxiety. Mediation analysis was performed using the med4way method.

Results: This longitudinal nationwide study leveraged the UK Biobank cohort to elucidate the protein-mediated effects of five major air pollutants on depression and anxiety. The findings identified 23 proteins mediating the risk of developing depression associated with air pollution, while no mediating proteins were found for anxiety. Additionally, the study discovered 38 proteins linked to the severity of anxiety related to air pollution and nine proteins connected to the severity of depressive symptoms. Notably, KEGG pathway analysis revealed significant associations with critical signaling cascades, such as the estrogen, IL-17, and pathways. Furthermore, STRING analysis underscored the shared roles of specific proteins, including EGFR, IL15, CCL2, and CCL20, in the context of air pollution-induced depression and anxiety, highlighting the involvement of immune-related processes and pathways.

Conclusion: The findings of this large population-based cohort study provide proteomic evidence on the mediating protein associations between air pollution and the onset of depression. The results suggest that the immune system plays a significant role in the biological mechanisms linking air pollution to depression and anxiety.

Background: This study aimed to investigate the potential mediation effect of adverse childhood school neighborhood friendship experiences (ACSNFEs) in the relationship between childhood parental emotions and depressive symptoms.

Methods: The study extracted data from 9489 participants from the China Health and Retirement Longitudinal Study (CHARLS) of 2014 and 2020. Depressive symptoms were assessed by the 10-item Center for Epidemiological Studies Depression Scale (CES-D-10). Stepwise regression based on least squares regression models, bootstrap tests, and Karlson–Holm–Breen (KHB)-based logit regression models were applied to analyze.

Results: Negative childhood parental emotions (β = 0.2030 and p < 0.001), negative childhood mother’s emotions (β = 0.3399 and p < 0.001), and negative childhood father’s emotions (β = 0.3866 and p < 0.001) were all significantly associated with higher severity of depressive symptoms. Bootstrap tests showed that the proportion of ACSNFEs mediated for childhood parental emotions was 14.03%. For childhood mother’s emotions and childhood father’s emotions, the mediating proportions were 15.32% and 13.57%, respectively. Moreover, KHB tests showed that the mediating effect still existed.

Conclusions: The association between childhood parental emotions and depressive symptoms was partly mediated by ACSNFEs. Focus on developing parental emotional management ability, actively guiding parents to help children develop high-quality friendships, and promoting the development of psychological health.

Background: Polycystic ovary syndrome (PCOS) is one of the most common endocrine disorders affecting women of reproductive age. It has been linked to a range of psychiatric disorders. Although premenstrual disorders (PMDs) are characterized by psychiatric symptoms in tandem with hormone changes controlled by the endocrine system, the association between PCOS and PMDs remains unknown.

Methods: We conducted a nationwide register-based cohort study including 2,965,178 females during 2001–2018 in Sweden. Individuals with PCOS were identified from clinical diagnoses recorded in the Swedish national registers (n = 41,515) and PMDs were identified based on clinical diagnoses and prescriptions with a clear indication of PMDs during follow-up. Using multivariable Cox regression, hazard ratio (HRs) of PMDs were estimated by comparing individuals with PCOS to those without. To account for confounders such as genetics or family environment, we conducted sibling comparison (N = 160,566).

Results: During a median follow-up of 15.3 years, 1308 (1.9%) individuals with PCOS had a premenstrual disorder (PMD) (4.67/1000 person-years). Compared to individuals without PCOS they had more than doubled risk of PMDs (age-adjusted HR: 2.26, 95% CI 2.14– 2.39). The association was attenuated after adjustment for demographic and socioeconomic factors as well as for comorbid psychiatric disorders and obesity yet remained significant (HR: 1.54, 95% CI 1.46–1.63). The sibling comparison showed similar findings (full-adjusted HR: 1.61, 95% CI 1.36–1.92). The association between PCOS and PMDs remained statistically significant regardless of the presence of psychiatric comorbidities, with HR of 1.33 (95% CI 1.20–1.47) for individuals with psychiatric comorbidities and 1.55 (95% CI 1.45–1.65) for those without.

Conclusions: Our findings suggest that individuals diagnosed with PCOS were at increased risk for PMDs. This association could not be entirely explained by shared risk factors, including such that sisters share.

Background: Subthreshold anxiety (STA) is a significant risk factor for developing anxiety disorder (AX), particularly in adolescence. Understanding the risk and protective factors of the development of STA in early life is essential for early prevention and intervention efforts. However, research on this topic is scarce.

Methods: We examined the data of 11,876 early adolescents from the Adolescent Brain and Cognitive Development (ABCD) Study to explore the factors influencing the development of STA between ages 9 and 13. The outcomes included developing AX, persistent STA, and remission from STA. Using the Child Behavior Checklist (CBCL), we identified 786 participants with STA. To predict STA transitions, we analyzed 31 diathesis-stress-related variables covering demographics, mental and physical health, and environmental factors, employing logistic regression.

Results: Compared to baseline healthy controls (HCs), adolescents with STA showed an odds ratio (OR) of 6.9 for converting to AX. The pivotal risk factors for progression from STA to AX were lack of perseverance and area deprivation, with females being more likely to maintain STA. Protective factors for a favorable prognosis of STA included the absence of traumatic history, lack of premeditation, increased physical activity, and positive school environment.

Conclusions: Healing traumatic experiences, increased physical activity, and enhancing school and family environments could help prevent adverse outcomes. By targeting these modifiable factors, adolescents at high risk can be identified and provided with interventions early in life.

Expectancy violation has been proposed as a potential core mechanism of action in psychotherapy, particularly in exposure therapy for anxiety disorders. However, various relevant expectations have been discussed, and empirical studies examining their significance are still scarce. This study aimed to investigate one specific form of expectancy violation, based on Rachman’s (1994) match-mismatch model, specifically by comparing expected and experienced fear and examining their relationship to safety behaviour during exposure in vivo in 268 patients meeting DSM-IV criteria for panic disorder with agoraphobia. Participants underwent exposure to a highly controlled manual-based cognitive behaviour therapy in a randomised multicenter psychotherapy study. Participants tended to overpredict fear during exposure. Both expected and experienced fear significantly decreased over the course of repeated exposure exercises, while prediction (in)accuracy (difference between expected and experienced fear) remained stable. The decrease in expected fear over time was a strong predictor of treatment outcomes for the Bodily Sensations Questionnaire (BSQ) and Panic and Agoraphobia Scale (PAS) at post. Even more, the reduction in expected fear was a significant predictor of treatment success across all outcome measures in the follow-up assessment. These findings suggest that violating excessive fear expectancies is not a necessary condition for symptom reduction during exposure therapy.

Background: Depressive and insomnia symptoms are common among older adults with chronic pain. We aimed to examine different chronic pain trajectories of older adults over an 8-year observation period and explore the network structures of depression and insomnia in each chronic pain group.

Methods: The trajectories of pain in the USA-based Health and Retirement Study (HRS) data from 2010 to 2018 were examined using latent class growth analyses (LCGA) method. Depressive and insomnia symptoms were measured with the eight-item version of the Center for Epidemiological Studies Depression (CESD-8) Scale and the four-item Jenkins Sleep Scale (JSS-4), respectively. Network models were constructed using the Ising model. Central symptoms and bridge symptoms were identified via expectedInfluence (EI) and bridge EI, respectively.

Results: A total of 11,132 older adults were included in the trajectory analysis, with three chronic pain trajectories identified, including “severe pain trajectory,” “moderate pain trajectory,” and “non or mild pain trajectory”. From these trajectories, “Lack of happiness” (CESD4), “Feeling depressed” (CESD1), and “Feeling sad” (CESD7) emerged as the most central symptoms, while “Feeling tired in the morning” (JSS4) was identified as the key bridge symptom. However, the findings may not be generalizable to other parts of the world outside the USA.

Conclusion: Older adults with different chronic pain trajectories exhibited similar depression and insomnia network structure. Implementing timely interventions that target central and bridge symptoms might mitigate the co-occurrence of depression and insomnia in this population.