Bridging Anxiety and Depression: A Network Approach in Anxious Adolescents

Assessing relinquishment of positivity as a central symptom bridging anxiety and depression

Anxiety and depression are often comorbid and chronic disorders. Previous research indicates that positivity relinquishment is a moderator of anxiety and depression, such that only anxious individuals who endorsed relinquishing positivity were also depressed. We sought to extend those findings by conducting three network analyses with self-report measures of anxiety, depression, activity avoidance, and perceived positivity of avoided activities (N = 104). We pre-registered our hypothesis for the first two networks that relinquishment of positivity would emerge as a central bridge symptom between anxiety and depressive symptoms. After combining redundant nodes, we estimated three networks and investigated the bridge symptoms in each network. Relinquishment of positivity bridged the symptom clusters in the first network, and avoidance of positivity was found to bridge the two symptom clusters of anxiety and depression in networks two and three. Additionally, an anhedonia circuit was uncovered in all three networks in which loss of interest/worthlessness, loss of energy, and loss of pleasure/pessimism connected to anxiety through relinquishment or avoidance. Our findings suggest that both relinquishment of positivity as well as avoidance of positivity could be potential pathways explaining the development and maintenance of anxiety and depression and should be properly targeted in treatment.

Edge-centric connectome-genetic markers of bridging factor to comorbidity between depression and anxiety

Depression-anxiety comorbidity is commonly attributed to the occurrence of specific symptoms bridging the two disorders. However, the significant heterogeneity of most bridging symptoms presents challenges for psychopathological interpretation and clinical applicability. Here, we conceptually established a common bridging factor (cb factor) to characterize a general structure of these bridging symptoms, analogous to the general psychopathological p factor. We identified a cb factor from 12 bridging symptoms in depression-anxiety comorbidity network. Moreover, this cb factor could be predicted using edge-centric connectomes with robust generalizability, and was characterized by connectome patterns in attention and frontoparietal networks. In an independent twin cohort, we found that these patterns were moderately heritable, and identified their genetic connectome-transcriptional markers that were associated with the neurobiological enrichment of vasculature and cerebellar development, particularly during late-childhood-to-young-adulthood periods. Our findings revealed a general factor of bridging symptoms and its neurobiological architectures, which enriched neurogenetic understanding of depression-anxiety comorbidity.

A network model of depressive and anxiety symptoms: a statistical evaluation

BACKGROUND

Although network analysis studies of psychiatric syndromes have increased in recent years, most have emphasized centrality symptoms and robust edges. Broadening the focus to include bridge symptoms within a systematic review could help to elucidate symptoms having the strongest links in network models of psychiatric syndromes. We conducted this systematic review and statistical evaluation of network analyses on depressive and anxiety symptoms to identify the most central symptoms and bridge symptoms, as well as the most robust edge indices of networks.

METHODS

A systematic literature search was performed in PubMed, PsycINFO, Web of Science, and EMBASE databases from their inception to May 25, 2022. To determine the most influential symptoms and connections, we analyzed centrality and bridge centrality rankings and aggregated the most robust symptom connections into a summary network. After determining the most central symptoms and bridge symptoms across network models, heterogeneity across studies was examined using linear logistic regression.

RESULTS

Thirty-three studies with 78,721 participants were included in this systematic review. Seventeen studies with 23 cross-sectional networks based on the Patient Health Questionnaire (PHQ) and Generalized Anxiety Disorder (GAD-7) assessments of clinical and community samples were examined using centrality scores. Twelve cross-sectional networks based on the PHQ and GAD-7 assessments were examined using bridge centrality scores. We found substantial variability between study samples and network features. 'Sad mood', 'Uncontrollable worry', and 'Worrying too much' were the most central symptoms, while 'Sad mood', 'Restlessness', and 'Motor disturbance' were the most frequent bridge centrality symptoms. In addition, the connection between 'Sleep' and 'Fatigue' was the most frequent edge for the depressive and anxiety symptoms network model.

CONCLUSION

Central symptoms, bridge symptoms and robust edges identified in this systematic review can be viewed as potential intervention targets. We also identified gaps in the literature and future directions for network analysis of comorbid depression and anxiety.

Prevalence and relevant factors of depression among adolescents in Xinjiang, China: A cross-sectional survey

The aim of this study is to elucidate the prevalence of depression and examine the contributing factors to depression among adolescents in Xinjiang, China. A stratified cluster sampling methodology was employed in this study, with the sample size determined through consideration of prior studies on adolescent depression. Employing this approach, 6 schools were chosen from each prefecture-level city, designated as urban areas, and 3 schools were selected from each county. Subsequently, individual classes were treated as units, and a minimum of 80 students from each grade were surveyed within the entire class. The investigation of adolescents involved the administration of a questionnaire assessing the factors influencing depression, along with the Center for Epidemiologic Studies Depression Scale (CES-D). Multivariate linear regression was used to analyze the influencing factors of depression. The occurrence rates of depression were 12.17%, 13.05%, 12.32%, and 9.29% in junior middle school, senior middle school, vocational high school, and college, respectively. The corresponding CES-D scores were 10.54 ± 8.26, 11.20 ± 8.37, 12.17 ± 6.94, and 11.33 ± 6.28. Significant associations with the CES-D score were observed for gender, smoking, alcohol consumption, and spending more than 4 hours online daily across the educational levels mentioned. The risk of experiencing depressive symptoms was elevated among female junior and senior high school students who spent more than 4 hours daily on the internet, engaged in cigarette smoking, and consumed alcohol. The findings underscore the significance of targeting high-risk groups, particularly through home-school collaborations, to mitigate excessive internet use and consequently reduce the likelihood of depressive symptoms in students.

Network analysis of depressive and anxiety symptoms in older Chinese adults with diabetes mellitus

Background

The move away from investigating mental disorders as whole using sum scores to the analysis of symptom-level interactions using network analysis has provided new insights into comorbidities. The current study explored the dynamic interactions between depressive and anxiety symptoms in older Chinese adults with diabetes mellitus (DM) and identified central and bridge symptoms in the depression-anxiety network to provide potential targets for prevention and intervention for depression and anxiety.

Methods

This study used a cross-sectional design with data from the 2017-2018 wave of the Chinese Longitudinal Healthy Longevity Survey (CLHLS). A regularized partial correlation network for depressive and anxiety symptoms was estimated based on self-reported scales completed by 1685 older adults with DM aged 65 years or older. Depressive and anxiety symptoms were assessed using the 10-item Center for Epidemiologic Studies Depression Scale (CESD-10) and the Seven-Item Generalized Anxiety Disorder Scale (GAD-7), respectively. Expected influence (EI) and bridge expected influence (BEI) indices were calculated for each symptom.

Results

According to cutoff scores indicating the presence of depression and anxiety, the prevalences of depression and anxiety in our sample were 52.9% and 12.8%, respectively. The comorbidity rate of depression and anxiety was 11.5%. The six edges with the strongest regularized partial correlations were between symptoms from the same disorder. "Feeling blue/depressed", "Nervousness or anxiety", "Uncontrollable worry", "Trouble relaxing", and "Worry too much" had the highest EI values. "Nervousness or anxiety" and "Everything was an effort" exhibited the highest BEI values.

Conclusion

Central and bridge symptoms were highlighted in this study. Targeting these symptoms may be effective in preventing the comorbidity of depressive and anxiety symptoms and facilitate interventions in older Chinese adults with DM who are at risk for or currently have depressive and anxiety symptoms.

Topographical similarity of cortical thickness represents generalized anxiety symptoms in adolescence

Generalized anxiety disorder (GAD) is a common condition characterized by excessive and uncontrollable worry, along with its high comorbidity rates. Despite increasing efforts to identify the neural underpinnings of GAD, neuroimaging research using cortical thickness have yielded largely inconsistent results. To address this, we adopted an inter-subject representational similarity analysis framework to explore a potential nonlinear relationship between vertex-wise cortical thickness and generalized anxiety symptom severity. We utilized a sample of 120 adolescents (13-18 years of age) from the Healthy Brain Network dataset. Here, we found greater topographical resemblance among participants with heightened generalized anxiety symptoms in the left caudal anterior cingulate and pericalcarine cortex. These results were not driven by the effects of age, sex, ADHD diagnosis, and GAD diagnosis. Such associations were not observed when including a group of younger participants (11-12 years of age) for analyses, highlighting the importance of age range selection when considering the link between cortical thickness and anxiety. Our findings reveal a novel cortical thickness topography that represents generalized anxiety in adolescents, which is embedded within the shared geometries between generalized anxiety symptoms and cortical thickness.

Congruency of multimodal data-driven personalization with shared decision-making for StayFine: individualized app-based relapse prevention for anxiety and depression in young people

Tailoring interventions to the individual has been hypothesized to improve treatment efficacy. Personalization of target-specific underlying mechanisms might improve treatment effects as well as adherence. Data-driven personalization of treatment, however, is still in its infancy, especially concerning the integration of multiple sources of data-driven advice with shared decision-making. This study describes an innovative type of data-driven personalization in the context of StayFine, a guided app-based relapse prevention intervention for 13- to 21-year-olds in remission of anxiety or depressive disorders (n = 74). Participants receive six modules, of which three are chosen from five optional modules. Optional modules are Enhancing Positive Affect, Behavioral Activation, Exposure, Sleep, and Wellness. All participants receive Psycho-Education, Cognitive Restructuring, and a Relapse Prevention Plan. The personalization approach is based on four sources: (1) prior diagnoses (diagnostic interview), (2) transdiagnostic psychological factors (online self-report questionnaires), (3) individual symptom networks (ecological momentary assessment, based on a two-week diary with six time points per day), and subsequently, (4) patient preference based on shared decision-making with a trained expert by experience. This study details and evaluates this innovative type of personalization approach, comparing the congruency of advised modules between the data-driven sources (1-3) with one another and with the chosen modules during the shared decision-making process (4). The results show that sources of data-driven personalization provide complementary advice rather than a confirmatory one. The indications of the modules Exposure and Behavioral Activation were mostly based on the diagnostic interview, Sleep on the questionnaires, and Enhancing Positive Affect on the network model. Shared decision-making showed a preference for modules improving positive concepts rather than combating negative ones, as an addition to the data-driven advice. Future studies need to test whether treatment outcomes and dropout rates are improved through personalization.

Prevalence, correlates, and network analysis of depression and its associated quality of life among ophthalmology nurses during the COVID-19 pandemic

Background

Nurses in Ophthalmology Department (OD) had a high risk of infection during the novel coronavirus disease 2019 (COVID-19) pandemic. This study examined the prevalence, correlates, and network structure of depression, and explored its association with quality of life (QOL) in Chinese OD nurses.

Methods

Based on a cross-sectional survey, demographic and clinical data were collected. Depression was measured with the 9-item Self-reported Patient Health Questionnaire (PHQ-9), and QOL was measured using the World Health Organization Quality of Life Questionnaire-brief version (WHOQOL-BREF). Univariate analyses, multivariate logistic regression analyses, and network analyses were performed.

Results

Altogether, 2,155 OD nurses were included. The overall prevalence of depression among OD nurses was 32.71% (95%CI: 30.73-34.70%). Multiple logistic regression analysis revealed that having family or friends or colleagues who were infected (OR = 1.760, p = 0.003) was significantly associated with higher risk of depression. After controlling for covariates, nurses with depression reported lower QOL (F(1, 2,155) = 596.784, p < 0.001) than those without depression. Network analyses revealed that 'Sad Mood', 'Energy Loss' and 'Worthlessness' were the key central symptoms.

Conclusion

Depression was common among OD nurses during the COVID-19 pandemic. Considering the negative impact of depression on QOL and daily life, regular screening for depression, timely counselling service, and psychiatric treatment should be provided for OD nurses, especially those who had infected family/friends or colleagues. Central symptoms identified in network analysis should be targeted in the treatment of depression.

Developmental Epidemiology of Pediatric Anxiety Disorders

This review summarizes the developmental epidemiology of childhood and adolescent anxiety disorders. It discusses the coronavirus disease of 2019 (COVID-19) pandemic, sex differences, longitudinal course, and stability of anxiety disorders in addition to recurrence and remission. The trajectory of anxiety disorders-whether homotypic (ie, the same anxiety disorder persists over time) or heterotypic (ie, an anxiety disorder shifts to a different diagnosis over time) is discussed with regard to social, generalized, and separation anxiety disorders as well as specific phobia, and panic disorder. Finally, strategies for early recognition, prevention, and treatment of disorders are discussed.

The Comorbidity of Depression and Anxiety Symptoms in Tinnitus Sufferers: A Network Analysis

OBJECTIVE

Sufferers of tinnitus, especially of the prolonged type, frequently suffer from comorbid depression and anxiety. From the perspective of the network model, this comorbidity is thought to be an interacting system of these two symptoms. In our study, we conducted a network analysis of depression and anxiety comorbidity in tinnitus sufferers, aiming to identify the central and bridge symptoms and make informed suggestions for clinical interventions and psychotherapy.

METHOD

A total of 566 tinnitus sufferers were enrolled in our study. The Patient Health Questionnaire-9 (PHQ-9) and the Generalized Anxiety Disorder 7-Item Questionnaire (GAD-7) were selected to evaluate depression and anxiety symptoms, respectively, followed by network analysis to construct the interacting networks.

RESULTS

The findings identified six edges of strongest regularized partial correlations in this network. Of these, three were depression symptoms and three were anxiety symptoms. The anxiety symptoms "Unable to control worry" and "Relaxation difficulty" and the depression symptom "Feeling depressed or hopeless" had the highest expected influence centrality. The analysis results also revealed three bridge symptoms: "Afraid something awful might happen", "Feeling of worthlessness", and "Trouble concentrating". As for "Suicidal ideation", the direct relations between this symptom and "Afraid something awful might happen" and "Feeling depressed or hopeless" were the strongest.

CONCLUSIONS

The central and bridge symptoms of the interacting network of depression and anxiety symptoms in tinnitus sufferers can be considered a significant transdiagnostic intervention target for the management of this comorbidity. In particular, clinical prevention and psychotherapy should be implemented, targeting the symptoms that have the strongest associations with suicidal ideation.

Psychological distress among women undergoing in vitro fertilization-embryo transfer: A cross-sectional and longitudinal network analysis

Background

Women undergoing in vitro fertilization-embryo transfer (IVF-ET) treatment were generally found to experience varying degrees of psychological distress across the treatment. Existing studies focused on total scores and diagnostic thresholds to characterize the symptoms' severity, which might hinder scientific progress in understanding and treating psychological distress.

Aims

We aimed to investigate (a) how depression and anxiety symptoms are interconnected within a network, and (b) the changes of the network (symptom connections and network centralities) over time, in women undergoing in vitro fertilization-embryo transfer.

Methods

A 4-wave longitudinal study was designed with 343 eligible women recruited from the Reproductive Medicine Center of a tertiary hospital in China. The network models were created to explore the relationship and changes between psychopathology symptoms both within and across anxiety and depression, with anxiety measured by the Generalized Anxiety Disorder-7 and depression measured by the Patient Health Questionnaire-9. Symptom network analysis was conducted to evaluate network and network properties, network centrality, and bridge centrality, as well as change trajectory network.

Results

For the strength centrality, "inability to control worry" and "worrying too much" were the most central symptoms at T1; however, these symptoms decreased. The centrality of "sadness" and "guilt" tended to increase steadily and became dominant symptoms. For bridge centrality indices, several bridge symptoms were identified separately from T1 to T4: "irritability," "concentration difficulties," "nervousness," and "restlessness;" "guilt" exhibited increased bridge symptoms. Furthermore, the change trajectory network indicated that "suicide ideation" became more closely related to guilt but not to worrying too much over time.

Conclusion

This study provides novel insights into the changes in central features, connections, and bridge symptoms during IVF-ET treatment and identified several bridge symptoms separately at different stages, which could activate the connection between psychopathology symptoms. The results revealed that sense of guilt was associated with worsening psychopathology symptoms, indicating that future psychological interventions should target guilt-related symptoms as a priority.

Network analysis of anxiety and depression in the functionally impaired elderly

Background

Evidence from previous studies has confirmed that functionally impaired elderly individuals are susceptible to comorbid anxiety and depression. Network theory holds that the comorbidity emerges from interactions between anxiety and depression symptoms. This study aimed to investigate the fine-grained relationships among anxiety and depression symptoms in the functionally impaired elderly and identify central and bridge symptoms to provide potential targets for intervention of these two comorbid disorders.

Methods

A total of 325 functionally impaired elderly individuals from five communities in Xi'an, China, were recruited for our investigation. The GAD-7 and PHQ-9 were used to measure anxiety and depression, respectively. SPSS 22.0 software was used for descriptive statistics, and R 4.1.1 software was used for network model construction, expected influence (EI) evaluation and bridge expected influence (BEI) evaluation.

Results

In the network, there were 35 edges (indicating partial correlations between symptoms) across the communities of anxiety and depression, among which the strongest edge was A1 "Nervousness or anxiety"-D2 "Depressed or sad mood." A2 "Uncontrollable worry" and D2 "Depressed or sad mood" had the highest EI values in the network, while A6 "Irritable" and D7 "Concentration difficulties" had the highest BEI values of their respective community. In the flow network, the strongest direct edge of D9 "Thoughts of death" was with D6 "Feeling of worthlessness."

Conclusion

Complex fine-grained relationships exist between anxiety and depression in functionally impaired elderly individuals. "Uncontrollable worry," "depressed or sad mood," "irritable" and "concentration difficulties" are identified as the potential targets for intervention of anxiety and depression. Our study emphasizes the necessity of suicide prevention for functionally impaired elderly individuals, and the symptom "feeling of worthlessness" can be used as an effective target.

Anxiolytic and antidepressive potentials of rosmarinic acid: A review with a focus on antioxidant and anti-inflammatory effects

Depression and anxiety are the most prevalent neuropsychiatric disorders that have emerged as global health concerns. Anxiolytic and antidepressant drugs, such as benzodiazepines, selective serotonin reuptake inhibitors, monoamine oxidase inhibitors, and tricyclics, are the first line used in treating anxiety and depression. Although these drugs lack efficacy and have a delayed response time and numerous side effects, their widespread abuse and market continue to grow. Over time, traditional practices using natural and phytochemicals as alternative therapies to chemical drugs have emerged to treat many pathological conditions, including anxiety and depression. Recent preclinical studies have demonstrated that the phenolic compound, rosmarinic acid, is effective against several neuropsychiatric disorders, including anxiety and depression. In addition, rosmarinic acid showed various pharmacological effects, such as cardioprotective, hepatoprotective, lung protective, antioxidant, anti-inflammatory, and neuroprotective effects. However, the potentialities of the use of rosmarinic acid in the treatment of nervous system-related disorders, such as anxiety and depression, are less or not yet reviewed. Therefore, the purpose of this review was to present several preclinical and clinical studies, when available, from different databases investigating the effects of rosmarinic acid on anxiety and depression. These studies showed that rosmarinic acid produces advantageous effects on anxiety and depression through its powerful antioxidant and anti-inflammatory properties. This review will examine and discuss the possibility that the anxiolytic and anti-depressive effects of rosmarinic acid could be associated with its potent antioxidant and anti-inflammatory activities.

Executive Functioning in Pediatric Anxiety and Its Relationship to Selective Serotonin Reuptake Inhibitor Treatment Response: A Double-Blind, Placebo-Controlled Trial

Objective: To characterize executive function in adolescents with generalized anxiety disorder (GAD) and its relationship to treatment. Methods: Using data from a double-blind, placebo-controlled trial of escitalopram in adolescents (N = 51) 12-17 years of age with GAD, we used the self-report version of the Behavior Rating Inventory of Executive Function (BRIEF-SR) to assess executive function, at baseline, and examined its relationship to treatment response as measured by the Pediatric Anxiety Rating Scale (PARS). Results: For all baseline subscores of the BRIEF-SR, T-scores were significantly elevated in adolescents with GAD compared to an age- and sex-matched normative healthy sample. In escitalopram-treated patients, baseline BRIEF-SR scores for Emotional Control (β = 0.256, 95% credibility interval [CrI]: 0.367 to 0.146, p < 0.001), Working Memory (β = 0.204, CrI: 0.2952 to 0.1134, p < 0.001), Planning/Organizing (β = -0.223, CrI: -0.1021 to -0.3436, p = 0.004), and Task Completion (β = -0.152, CrI: 0.075 to 0.228, p = 0.002) predicted the trajectory of improvement in PARS score over the 8-week trial. For youth who received placebo, only the Inhibit score was significantly, but weakly, associated with response trajectory (β = -0.081, CrI: -0.0167 to -0.1461, p = 0.015). For adolescents who had clinically significant impairment in Emotional Control, Working Memory, Planning/Organizing, and Task Completion (i.e., T-score >65), the trajectory of improvement significantly differed from patients without scores in the clinically significant range. Conclusions: Taken together, these findings point to the potential value of assessing executive function in youth with anxiety disorders as one strategy for guiding treatment selection. These data suggest that executive function may predict treatment response to psychopharmacologic treatment and point to numerous avenues for further personalizing treatment.

Symptom-level networks of youth- and parent-reported depression and anxiety in a transdiagnostic clinical sample

Depression and anxiety disorders confer a significant public health concern for youth and their co-occurrence places youth at a higher risk for poorer psychosocial outcomes. In the present study, we use network analysis to investigate the role of and interactions among individual depression and anxiety symptoms in a treatment-seeking clinical sample.

METHODS

We estimate regularized partial correlation networks for youth- and parent reported symptoms in a transdiagnostic sample of youth (N = 417, ages 8-18). We examined features of the symptom-level networks such as network stability, centrality, bridge symptoms, and communities in both youth- and parent-reported networks.

RESULTS

Results indicate stable networks with disorder-specific clustering, such that symptoms were more interconnected within compared to between disorders. Symptoms related to self-comparison to peers and negative views of the future were most central in both networks. Symptoms of depression and anxiety were connected by worries for the future and hopelessness in the youth-reported network, whereas self-comparison to peers and low self-efficacy were bridge symptoms in the parent network. Distinct symptom clusters emerged in the parent- and youth-reported networks.

CONCLUSIONS

Our findings indicate that negative self-evaluation, negative views of the future, and repetitive negative thinking more generally are influential symptoms in the presentation and co-occurrence of depression and anxiety and as such may be promising targets in the treatment and prevention of depression and anxiety in youth.

Identification of cohesive subgroups in a university hall of residence during the COVID-19 pandemic using a social network analysis approach

THE AIMS

(i) analyze connectivity between subgroups of university students, (ii) assess which bridges of relational contacts are essential for connecting or disconnecting subgroups and (iii) to explore the similarities between the attributes of the subgroup nodes in relation to the pandemic context. During the COVID-19 pandemic, young university students have experienced significant changes in their relationships, especially in the halls of residence. Previous research has shown the importance of relationship structure in contagion processes. However, there is a lack of studies in the university setting, where students live closely together. The case study methodology was applied to carry out a descriptive study. The participation consisted of 43 university students living in the same hall of residence. Social network analysis has been applied for data analysis. Factions and Girvan-Newman algorithms have been applied to detect the existing cohesive subgroups. The UCINET tool was used for the calculation of the SNA measure. A visualization of the global network will be carried out using Gephi software. After applying the Girvan-Newman and Factions, in both cases it was found that the best division into subgroups was the one that divided the network into 4 subgroups. There is high degree of cohesion within the subgroups and a low cohesion between them. The relationship between subgroup membership and gender was significant. The degree of COVID-19 infection is related to the degree of clustering between the students. College students form subgroups in their residence. Social network analysis facilitates an understanding of structural behavior during the pandemic. The study provides evidence on the importance of gender, race and the building where they live in creating network structures that favor, or not, contagion during a pandemic.

Network Analysis of Insomnia in Chinese Mental Health Professionals During the COVID-19 Pandemic: A Cross-Sectional Study

PURPOSE

The coronavirus disease 2019 (COVID-19) pandemic is associated with increased risk of insomnia symptoms (insomnia hereafter) in health-care professionals. Network analysis is a novel approach in linking mechanisms at the symptom level. The aim of this study was to characterize the insomnia network structure in mental health professionals during the COVID-19 pandemic.

PATIENTS AND METHODS

A total of 10,516 mental health professionals were recruited from psychiatric hospitals or psychiatric units of general hospitals nationwide between March 15 and March 20, 2020. Insomnia was assessed with the insomnia severity index (ISI). Centrality index (ie, strength) was used to identify symptoms central to the network. The stability of network was examined using a case-dropping bootstrap procedure. The network structures between different genders were also compared.

RESULTS

The overall network model showed that the item ISI7 (interference with daytime functioning) was the most central symptom in mental health professionals with the highest strength. The network was robust in stability and accuracy tests. The item ISI4 (sleep dissatisfaction) was connected to the two main clusters of insomnia symptoms (ie, the cluster of nocturnal and daytime symptoms). No significant gender network difference was found.

CONCLUSION

Interference with daytime functioning was the most central symptom, suggesting that it may be an important treatment outcome measure for insomnia. Appropriate treatments, such as stimulus control techniques, cognitive behavioral therapy and relaxation training, could be developed. Moreover, addressing sleep satisfaction in treatment could simultaneously ameliorate daytime and nocturnal symptoms.

Altered gray matter structural covariance networks in postpartum depression: a graph theoretical analysis

BACKGROUND

Postpartum depression (PPD) is a serious postpartum mental health problem worldwide. To date, minimal is known about the alteration of topographical organization in the brain structural covariance network of patients with PPD. This study investigates the brain structural covariance networks of patients with PPD by using graph theoretical analysis.

METHODS

High-resolution 3D T1 structural images were acquired from 21 drug-naive patients with PPD and 18 healthy postpartum women. Cortical thickness was extracted from 64 brain regions to construct the whole-brain structural covariance networks by calculating the Pearson correlation coefficients, and their topological properties (e.g., small-worldness, efficiency, and nodal centrality) were analyzed by using graph theory. Nonparametric permutation tests were further used for group comparisons of topological metrics. A node was set as a hub if its betweenness centrality (BC) was at least two standard deviations higher than the mean nodal centrality. Network-based statistic (NBS) was used to determine the connected subnetwork.

RESULTS

The PPD and control groups showed small-worldness of group networks, but the small-world network was more evidently in the PPD group. Moreover, the PPD group showed increased network local efficiency and almost similar network global efficiency. However, the difference of the network metrics was not significant across the range of network densities. The hub nodes of the patients with PPD were right inferior parietal lobule (BC = 13.69) and right supramarginal gyrus (BC = 13.15), whereas those for the HCs were left cuneus (BC = 14.96), right caudal anterior-cingulate cortex (BC = 15.51), and right precuneus gyrus (BC = 15.74). NBS demonstrated two disrupted subnetworks that are present in PPD: the first subnetwork with decreased internodal connections is mainly involved in the cognitive-control network and visual network, and the second subnetwork with increased internodal connections is mainly involved in the default mode network, cognitive-control network and visual network.

CONCLUSIONS

This study demonstrates the alteration of topographical organization in the brain structural covariance network of patients with PPD, providing in sight on the notion that PPD could be characterized as a systems-level disorder.