Depression and Anxiety最新文献

{"title":"From the p-Factor to Cognitive Content: Detection and Discrimination of Psychopathologies Based on Explainable Artificial Intelligence","authors":"Erkan Eyrikaya,&nbsp;İhsan Dağ","doi":"10.1155/da/9943590","DOIUrl":"https://doi.org/10.1155/da/9943590","url":null,"abstract":"<div>\u0000 <p><b>Background and Aims:</b> Differentiating psychopathologies is challenging due to shared underlying mechanisms, such as the <i>p</i>-factor. Nevertheless, recent methodological advances suggest that distinct linguistic markers can help detect and differentiate these conditions. This study aimed to use cognitive content analysis with advanced natural language processing (NLP) and machine learning (ML) to (Study 1) distinguish among control, depression, anxiety, and depressive-anxiety groups and (Study 2) detect general psychopathology.</p>\u0000 <p><b>Methods:</b> Data from 1901 participants (retained from 2551 respondents aged 18–43 years who completed the Beier sentence completion test [BSCT]) were analyzed. For Study 1, groups were formed using the Depression, Anxiety, and Stress Scale (DASS-21); negative mood was assessed via the Positive and Negative Affect Schedule (PANAS). For Study 2, the Brief Symptom Inventory (BSI) categorized general psychopathology and self-reported diagnostic status served as external validation. Two analytic approaches were employed: (1) textual analysis with a bidirectional encoder representations from transformers (BERT) model and (2) subscale-score analysis using a support vector machine (SVM). SHapley Additive exPlanations (SHAP) interpreted the ML models.</p>\u0000 <p><b>Results:</b> In Study 1, the models distinguished control, depression, anxiety, and depressive-anxiety groups. Anxiety was marked by positive content, hope, and I-Talk, whereas depression involved negative, hopeless content. Depressive-anxiety combined features of anxiety with a pronounced negative outlook, suggesting a transitional phase where diminishing hope may bridge anxiety to depression. In Study 2, the models performed high in distinguishing the self-reported pathology diagnosis group (area under the curve [AUC]: 0.81 [BERT], 0.85 [SVM]) from subclinical samples but failed to differentiate the self-reported past diagnosis (AUC: 0.53 [BERT], 0.57 [SVM]) group from controls. This implies that cognitive changes in psychopathology may share a consistent underlying structure like <i>p</i>-factor.</p>\u0000 <p><b>Conclusion:</b> These pioneer findings demonstrate that integrating advanced computational techniques can identify key linguistic markers and guide the development of language-based diagnostic tools, potentially transforming mental health diagnostics.</p>\u0000 </div>","PeriodicalId":55179,"journal":{"name":"Depression and Anxiety","volume":"2025 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/da/9943590","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144091760","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Depression in Adolescence: Relevance of Serotonin Receptor Polymorphisms","authors":"Giulia Gizzi,&nbsp;Federico Fiorani,&nbsp;Elisabetta Albi,&nbsp;Samuela Cataldi,&nbsp;Claudia Mazzeschi,&nbsp;Elisa Delvecchio","doi":"10.1155/da/5239931","DOIUrl":"https://doi.org/10.1155/da/5239931","url":null,"abstract":"<div>\u0000 <p>Depression in adolescence is influenced by the environment, family members, social relationships, and genetic factors. Gene polymorphisms of serotonin receptors were associated with mental/psychiatric disorders, including impulsive, aggressive, violent, antisocial or criminal conduct, schizophrenia, eating disorders, alexithymia, autism, and major depressive disorder (MDD). Few studies reported the association between serotonin receptor polymorphisms and depressive symptoms in nonclinical subjects. The present study aimed to evaluate the serotonin receptor polymorphisms in nonclinical adolescents presenting depressive symptoms. The results clearly demonstrated that nonclinical adolescents with severe depressive symptoms had a high concentration of GA + AA in the recessive model and of AA in the homozygous model of the rs6311 polymorphism. The data indicated that the A allele was associated with severe depressive symptoms. Moreover, the analysis highlighted a trend of association of TT + CT in the recessive model for rs6313 polymorphism and severe symptoms. In conclusion, our study confirms that the A allele for rs6311 represents a risk factor, and the allele T for rs6313 could be a possible risk factor for severe depressive symptoms. As a consequence, the allele G for rs6311 and the allele C for rs6313 could be protective against severe depressive symptoms. Therefore, it might be appropriate to work preventively on adolescents with the A allele for rs6311 and T allele for rs6313 polymorphism to reduce the possibility of developing depressive symptoms and to preserve mental health in young people.</p>\u0000 </div>","PeriodicalId":55179,"journal":{"name":"Depression and Anxiety","volume":"2025 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/da/5239931","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144085286","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Association Between Socioeconomic Status and Neuropsychiatric Symptoms in the UK Biobank: The Moderating Role of Sociability","authors":"Jiahui Xiao,&nbsp;Bingqing Guo,&nbsp;Yuxin Ma,&nbsp;Ninghao Huang,&nbsp;Tao Huang,&nbsp;Hailun Liang","doi":"10.1155/da/1293449","DOIUrl":"https://doi.org/10.1155/da/1293449","url":null,"abstract":"<div>\u0000 <p><b>Introduction:</b> Neuropsychiatric symptoms are signs of cognitive decline and associated disorders. The effects of socioeconomic status and social interaction on cognitive decline have already been well documented. Accordingly, the present study aimed to build on the work investigating those factors and cognitive health by examining the relationships between socioeconomic status, sociability, and neuropsychiatric symptoms.</p>\u0000 <p><b>Methods:</b> Data from the UK Biobank (<i>N</i> = 301,848) were subjected to logistic regressions to examine the relationship between socioeconomic status, sociability, and neuropsychiatric symptoms and sociability to identify any potential moderator in the socioeconomic status-neuropsychiatric symptoms relationship. Specifically, socioeconomic status was defined by the Townsend deprivation index, while sociability was constructed using a cumulative score of four aspects. Meanwhile, neuropsychiatric symptoms were represented by depression, anxiety, and irritability, each of which had a genetic risk score calculated.</p>\u0000 <p><b>Results:</b> Individuals who reported lower socioeconomic status also reported more depression and anxiety, while those with higher sociability reported fewer depression and anxiety. Further, it was found that sociability moderated the relationship between socioeconomic status and two symptoms: depression and anxiety. No significant moderating effects were found regarding irritability.</p>\u0000 <p><b>Conclusion:</b> The study results indicate the need for interventions aimed at neuropsychiatric symptoms to reduce possible cognitive disorders. They also demonstrate the need to eliminate economic and social disparities and the importance of improving sociability.</p>\u0000 </div>","PeriodicalId":55179,"journal":{"name":"Depression and Anxiety","volume":"2025 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/da/1293449","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143949785","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Profiles and Transitions of Sleep Disturbance and Depression Among Chinese Adolescents: The Predictive Roles of Life Stress and Resilience","authors":"Dan Chen,&nbsp;Haoxian Ye,&nbsp;Luowei Bu,&nbsp;Wenxu Liu,&nbsp;Dongfang Wang,&nbsp;Fang Fan","doi":"10.1155/da/3253107","DOIUrl":"https://doi.org/10.1155/da/3253107","url":null,"abstract":"<div>\u0000 <p><b>Purposes:</b> Sleep disturbance and depression co-occur frequently, yet their co-occurring and transitional nature among adolescents remains underexplored. Meanwhile, few studies have examined the potential predictive effect of environmental factors (e.g., life stress) and individual factors (e.g., resilience) on their interactive profiles and transitions. This study investigated the profiles and transitions of sleep disturbance and depression for Chinese adolescents, along with the predictive role of life stress and resilience in profiles and transitions.</p>\u0000 <p><b>Methods:</b> A total of 17,404 adolescents (<i>M</i>_age = 12.1 ± 1.2 years, ranging from 10 to 17 years; 48.4% of females) were assessed at baseline from April 21 to May 12, 2021 (Time 1, T1), 6 months later from December 17–26, 2021 (Time 2, T2), and 1 year later from May 17 to June 6, 2022 (Time 3, T3). We used latent profile and latent transition analysis (LTA) to explore sleep disturbance and depression profiles and their transitions over time. Multivariate logistic regression was conducted to prove the predictive roles of stress and resilience in these profiles and transitions.</p>\u0000 <p><b>Results:</b> Across all three time points, three profiles were consistently identified: low profile, co-occurring moderate profile, and co-occurring high profile. Three profiles presented distinct transition patterns, with adolescents in co-occurring high profiles displaying the highest level of transitions. The logistic regression suggested that adolescents with more interpersonal and academic stress or less resilience were more likely to belong to or transition into at-risk profiles.</p>\u0000 <p><b>Conclusion:</b> Recognizing subgroup differences is crucial to understanding the co-occurrence and transitions of sleep disturbance and depression. Stress and resilience, particularly interpersonal stress, are significant predictors. This underscores the need importance for dynamically monitoring changes in sleep disturbance and depression, as well as identifying resilience and stress factors, which are essential for developing intervention programs.</p>\u0000 </div>","PeriodicalId":55179,"journal":{"name":"Depression and Anxiety","volume":"2025 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/da/3253107","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143944805","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine Learning Models to Identify Clinically Significant Anxiety in Short-Term Insomnia Using Accelerometers","authors":"Leqin Fang,&nbsp;Weixiong Zeng,&nbsp;Shuqiong Zheng,&nbsp;Shixu Du,&nbsp;Hangyi Yang,&nbsp;Xue Luo,&nbsp;Shufei Zeng,&nbsp;Zhiting Huang,&nbsp;Weiguo Chen,&nbsp;Bin Zhang","doi":"10.1155/da/3082856","DOIUrl":"https://doi.org/10.1155/da/3082856","url":null,"abstract":"<div>\u0000 <p>Clinically significant anxiety (CSA) is common in individuals with short-term insomnia. This study aims to explore the relationship between CSA and the subjective and objective parameters of sleep in patients with short-term insomnia and construct machine learning (ML) models to determine the utility of accelerometer features in identifying significant anxiety. A total of 205 short-term insomnia participants from China were assigned to the group with CSA (<i>N</i> = 33) or the group without CSA (<i>N</i> = 172). Interaction analysis based on linear regression was used to estimate the possible interactive effect of accelerometer features between CSA and sleep problems. Four feature sets and eight algorithms were used to construct ML models, with Shapley Additive exPlanations (SHAP) values used to visualize feature importance and influence processes. CSA in patients with short-term insomnia leads to more severe subjective sleep problems, and accelerometer-measured features warrant further attention for the identification of interactive factors. A significant interaction effect was found between anxiety symptoms and longer duration of physical activity on insomnia severity (<i>P</i>_interaction &lt; 0.05). Anxiety symptoms and interdaily stability had an interactive association with sleep hygiene behaviors (<i>P</i>_interaction &lt; 0.01). ML can process and analyze complex accelerometer features to identify CSA in patients with short-term insomnia. Compared with other feature sets and algorithms, the XGBoost model with accelerometer-measured features on weekdays more effectively identified CSA with area under the curve (AUC) value of 0.777. SHAP analysis results indicated that circadian rhythm features had significant contributions. Decision plots based on SHAP were applied to visualize the personalized risk factors for each patient and provide clinicians with more easily understandable and practical explanation methods that enhance clinical decision-making.</p>\u0000 <p><b>Trial Registration:</b> Chinese Clinical Trial Registry identifier: ChiCTR2200062910</p>\u0000 </div>","PeriodicalId":55179,"journal":{"name":"Depression and Anxiety","volume":"2025 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/da/3082856","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143944806","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Association Between High Levels of Aggression and Insomnia in Chinese Adolescents: A Longitudinal Latent Profile Analysis","authors":"Sihong Li,&nbsp;Hui Chen,&nbsp;Xianliang Chen,&nbsp;Huajia Tang,&nbsp;Yanyue Ye,&nbsp;Jiansong Zhou","doi":"10.1155/da/3713624","DOIUrl":"https://doi.org/10.1155/da/3713624","url":null,"abstract":"<div>\u0000 <p><b>Background:</b> Aggression has been reported to be associated with insomnia in adolescents. However, the impact of aggression and different levels of aggression on insomnia needs further exploration. This study aimed to explore the association of aggression, as well as different profiles of aggression, with insomnia in Chinese adolescents.</p>\u0000 <p><b>Method:</b> This was a prospective cohort study with an 8-month follow-up period. The Short-Form Buss–Perry Aggression Questionnaire (BPAQ-SF) was used to assess the aggression; the Insomnia Severity Index (ISI) was used to assess the symptoms of insomnia. Latent profile analysis (LPA) was conducted to identify profiles of aggression. The association between different profiles of aggression and insomnia was assessed using logistic regression analysis. We also used the restricted cubic spline model to investigate the pattern of the association.</p>\u0000 <p><b>Results:</b> A total of 1124 students completed the questionnaire. The aggression was classified into three profiles: low aggression (<i>n</i> = 931, 82.8%), moderate aggression (<i>n</i> = 153, 13.6%), and high aggression (<i>n</i> = 40, 3.6%). A follow-up survey after 8 months found 228 (20.3%) new cases of insomnia. Moreover, high aggression was associated with a significantly increased risk of insomnia after adjustment for age, sex, ethnicity, anxiety state, and depressive state (odds ratio [OR]: 9.98, 95%CI: 4.94–20.15). The relationship between aggression and the risk of insomnia was linear in the restricted cubic spline regression analysis.</p>\u0000 <p><b>Conclusion:</b> High levels of aggression were significantly associated with insomnia among Chinese adolescents. Therefore, targeted interventions aimed at addressing insomnia among adolescents with high levels of aggression are needed to improve their mental well-being.</p>\u0000 </div>","PeriodicalId":55179,"journal":{"name":"Depression and Anxiety","volume":"2025 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/da/3713624","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143944804","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mapping the Dynamics of Generalized Anxiety Symptoms and Actionable Transdiagnostic Mechanisms: A Panel Study","authors":"Asle Hoffart,&nbsp;Nora Skjerdingstad,&nbsp;René Freichel,&nbsp;Sverre Urnes Johnson,&nbsp;Sacha Epskamp,&nbsp;Omid V. Ebrahimi","doi":"10.1155/da/1885004","DOIUrl":"https://doi.org/10.1155/da/1885004","url":null,"abstract":"<div>\u0000 <p><b>Background:</b> The long-term dynamic interaction between symptoms of generalized anxiety disorder (GAD) and their theorized mechanistic processes derived from three treatment models of GAD—the emotion dysregulation model, the model underlying metacognitive therapy (MCT), and the intolerance of uncertainty model—was investigated.</p>\u0000 <p><b>Methods:</b> Four data waves 2 months apart were delivered by a representative population sample of 4361 participants during the COVID-19 pandemic in Norway. Networks were estimated using the newly developed panel graphical vector autoregression (panel-GVAR) methods.</p>\u0000 <p><b>Results:</b> In the temporal network, and consistent with processes stipulated in the metacognitive model, the experience that worry is uncontrollable predicted the GAD symptom fear of awful events, which in turn predicted a range of other GAD symptoms, that is, anxiety, restlessness, and irritability. Fear of awful events had high outstrength, that is, predicted other variables to a large degree. Inconsistent with the metacognitive model, the coping strategy thought suppression negatively predicted restlessness. Consistent with the emotion dysregulation model, emotion dysregulation predicted avoidance. No relationships proposed by the intolerance of uncertainty model of GAD were identified in the temporal network. The contemporaneous network was dense with nodes clustering according to the constructs they belonged to.</p>\u0000 <p><b>Conclusions:</b> The findings indicate the importance of the theory-derived variables, the experience and belief that worry is uncontrollable and emotion dysregulation, as potential targets for intervention to alleviate GAD symptoms. The findings also indicate that uncontrollability of worry and fear of awful events should be considered central symptoms of GAD in a within-individual diagnostics supplementary to current diagnostic manuals, such as the Diagnostic and Statistical Manual of Mental Disorders 5th edition (DSM-5).</p>\u0000 </div>","PeriodicalId":55179,"journal":{"name":"Depression and Anxiety","volume":"2025 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/da/1885004","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143938881","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Association Between Abnormal Plasma Lipid Metabolism and Psychological Characteristics in Adolescents With Major Depressive Disorder","authors":"Yuxin Wang,&nbsp;Hui Chen,&nbsp;Jinfeng Wang,&nbsp;Shurui Chen,&nbsp;Jiali Liu,&nbsp;Xianliang Chen,&nbsp;Sihong Li,&nbsp;Huajia Tang,&nbsp;Jiawei Zhou,&nbsp;Yanyue Ye,&nbsp;Yusheng Tian,&nbsp;Xiaoping Wang,&nbsp;Jiansong Zhou","doi":"10.1155/da/5564796","DOIUrl":"https://doi.org/10.1155/da/5564796","url":null,"abstract":"<div>\u0000 <p><b>Background:</b> Major depressive disorder (MDD) in adolescents is a significant global public health issue, yet its pathophysiological mechanism remains unclear. Although changes in lipid metabolites have been observed in people with MDD, most relevant studies focus on adults, with limited research on adolescents. Furthermore, little is known about how interactions between metabolites and psychosocial factors contribute to MDD among adolescents. This study aimed to explore the relationship between lipid metabolism and psychological characteristics in adolescents with MDD to provide insights into its biological mechanisms.</p>\u0000 <p><b>Methods:</b> A cross-sectional study was conducted on 40 adolescents with MDD patients and 20 healthy controls (HCs). Plasma samples were analyzed using ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) for targeted lipidomics. Spearman analysis was employed to examine the correlation between differentially expressed lipids and the psychological characteristics of participants.</p>\u0000 <p><b>Results:</b> We identified significant differences in 37 lipid species, including glycerophospholipids (GPs), glycerolipids (GLs), and sphingolipids (SPs), with a specific focus on lysophosphatidylcholine (LPC; 18:0), which demonstrated high diagnostic potential (area under the curve (AUC) = 0.886). Pathway analysis revealed significant disturbances in GP metabolism. Spearman correlation analysis showed that most differential lipid metabolites were negatively correlated with scores of depressive symptoms, childhood maltreatment (CM), extraversion, and neuroticism, while positively correlated with scores of psychoticism and positive coping in adolescents with MDD.</p>\u0000 <p><b>Conclusions:</b> The study showed that adolescents with MDD presented a significantly differentiated profile of plasma lipidomics compared to HCs. These findings may contribute to a better understanding of the role of lipid metabolism in adolescent MDD.</p>\u0000 </div>","PeriodicalId":55179,"journal":{"name":"Depression and Anxiety","volume":"2025 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/da/5564796","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143938865","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Role of Temperament Traits in Bipolar Disorder: Neuroimaging Study","authors":"Kirill Markin,&nbsp;Artem Trufanov,&nbsp;Dmitriy Tarumov,&nbsp;Alexander Krasichkov,&nbsp;Yulia Shichkina,&nbsp;Mikhail Kupriyanov","doi":"10.1155/da/5974860","DOIUrl":"https://doi.org/10.1155/da/5974860","url":null,"abstract":"<div>\u0000 <p><b>Purpose:</b> This study aimed to identify temperament traits alterations in bipolar disorder (BD) and explore their potential neuroimaging correlates using resting-state functional magnetic resonance imaging.</p>\u0000 <p><b>Methods:</b> We assessed seed-to-voxel alterations in four large-scale brain networks (Salience, Frontoparietal, Default Mode, and SensoriMotor) in 49 patients with BD and 49 healthy individuals according to the difference of temperamental traits (Reward Dependence, Novelty Seeking, Harm Avoidance, and Persistence). Also, we measured the relationship of temperamental traits with the severity of manic and depressive symptoms and impulsivity.</p>\u0000 <p><b>Results:</b> Lower Reward Dependence (t-Welch’s (87.1) = −2.50; <i>p</i> = 0.014) in bipolar patients was associated with increased functional connectivity between Salience Network and Default Mode and FrontoParietal Networks. Higher Novelty Seeking (t-Welch’s (87.3) = 4.37; <i>p</i> &lt; 0.001) was associated with increased functional connectivity within FrontoParietal Network, whereas its functional connectivity with Visual and Dorsal Attention Networks was decreased. Higher Harm Avoidance (t-Welch’s (82.8) = 4.85; <i>p</i> &lt; 0.001) was associated with increased functional connectivity between FrontoParietal Network and basal ganglia. Lower Persistence (<i>U</i> = 998; <i>p</i> = 0.002) was associated with decreased functional connectivity within FrontoParietal Network and with Default Mode Network. Higher persistence in bipolar patients was associated with greater severity of manic symptoms (Spearman’s rho = 0.302, <i>p</i> = 0.018), while lower Reward Dependence was associated with increased severity of depressive symptoms (Pearson’s <i>r</i> = −0.388, <i>p</i> = 0.003). Harm Avoidance negatively correlates with Persistence (Pearson’s <i>r</i> = −0.525, <i>p</i> &lt; 0.001) and positively with reward dependence (Pearson’s <i>r</i> = −0.259, <i>p</i> = 0.036). We also found a negative correlation between impulsivity and Reward Dependence (Pearson’s <i>r</i> = −0.312, <i>p</i> = 0.029) and positive correlation between impulsivity and Novelty Seeking (Pearson’s <i>r</i> = 0.525, <i>p</i> &lt; 0.001).</p>\u0000 <p><b>Conclusions:</b> The findings demonstrate a possible functional neuroimaging basis for altered temperamental traits in patients with bipolar disorder.</p>\u0000 </div>","PeriodicalId":55179,"journal":{"name":"Depression and Anxiety","volume":"2025 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/da/5974860","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143930451","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Association Between Body Mass Index and Comorbid Anxiety in First-Episode and Drug Naïve Patients With Major Depressive Disorder","authors":"Shilin Liu,&nbsp;Yu Huang,&nbsp;Aixin Liu,&nbsp;Xiaoxuan Li,&nbsp;Yifan Fu,&nbsp;Wei Wang,&nbsp;Yuechun Wen,&nbsp;Tao Jiang,&nbsp;Xiangyang Zhang","doi":"10.1155/da/6648190","DOIUrl":"https://doi.org/10.1155/da/6648190","url":null,"abstract":"<div>\u0000 <p><b>Objective:</b> There is limited evidence regarding the relationship between body mass index (BMI) and anxiety symptoms in individuals with major depressive disorder (MDD), and the findings are controversial. This study aimed to explore the association between BMI and anxiety symptoms in patients with first-episode drug-naïve (FEDN) MDD.</p>\u0000 <p><b>Methods:</b> A total of 1718 FEDN MDD patients were included in this study, gathering information on their sociodemographic attributes and physical measurements. BMI was classified into three categories (normal, overweight, and obese) based on the standards of the Working Group on Obesity in China (WGOC). Logistic regression and double robust estimation were used to assess the association between anxiety symptoms and BMI. Additionally, a restricted cubic spline (RCS) analysis was used to examine the relationship between anxiety symptoms and BMI. If nonlinear associations existed, threshold effects were analyzed using a two-piecewise logistic regression model. The subgroup analysis was performed to validate the robustness of the findings.</p>\u0000 <p><b>Results:</b> Among 1718 patients, 12.7% (218) exhibited anxiety symptoms. After adjusting for confounding variables, multivariable logistic regression analysis revealed a positive association between BMI and the risk of experiencing anxiety symptoms (OR = 1.13, 95% CI: 1.039–1.229, <i>p</i> = 0.004). These findings were further confirmed using a doubly robust estimation. Additionally, RCS analysis revealed a nonlinear correlation between BMI and anxiety symptoms, with a turning point of 26.9 kg/m². On the left side of the inflection point, a positive association between BMI and anxiety symptoms was detected (OR = 1.167, 95% CI: 1.055–1.296, <i>p</i> = 0.003), while no significant association was observed on the right side of the inflection point (OR = 1.01, 95% CI: 0.685–1.341, <i>p</i> = 0.972). Subgroup analyses revealed significant variations in the association between gender and education level.</p>\u0000 <p><b>Conclusion:</b> This study demonstrated that a higher BMI was associated with an increased risk of experiencing anxiety symptoms in Chinese patients with FEDN MDD, particularly among those with a BMI below 26.9 kg/m².</p>\u0000 </div>","PeriodicalId":55179,"journal":{"name":"Depression and Anxiety","volume":"2025 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/da/6648190","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143930450","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}