Major Depressive Disorder Symptom Severity Research Articles

Altered resting-state brain activity of the superior parietal cortex and striatum in major depressive disorder and schizophrenia

BackgroundResting-state functional magnetic resonance imaging (fMRI) studies have shown altered brain activity in major depressive disorder (MDD) and schizophrenia (SZ). Despite differing diagnoses, SZ and MDD share similar features. However, functional brain activity similarities and differences between SZ and MDD remain unclear. MethodsParticipants with MDD, SZ, and normal controls (n=36 each) underwent resting-state fMRI scans. Amplitude of low-frequency fluctuations (ALFF) was used to analyze the preprocessed rs-fMRI data. One-way ANOVAs and post hoc analyses compared ALFF values in different brain regions. Pearson correlation analysis examined associations with clinical symptoms. ResultsComparison among the three groups revealed significant differences in ALFF values within the left superior parietal cortex (L-SPC) and bilateral striatum. Through pairwise comparisons, patients with SZ but not patients with MDD were found to exhibit increased striatum ALFF values relative to NC individuals, but decreased in MDD. Meanwhile, L-SPC ALFF values were significantly increased in patients with SZ relative to both normal control individuals and patients with MDD, while no differences in these values were observed between the normal control and MDD groups. The Pearson correlation analyses showed significant positive correlations between ALFF in the striatum and PANSS positive score, but no significant correlation with other symptom severity in SZ and MDD. ConclusionThese findings support the hypothesis of alterations in brain functional activity as a fundamental component of the pathogenesis of MDD and SZ. The observed differences in functional brain activity in the superior parietal cortex and striatum between MDD and SZ provide a neuroimaging basis that can contribute to the differential diagnosis of these debilitating conditions.

Quantitative MRI at 7-Tesla reveals novel frontocortical myeloarchitecture anomalies in major depressive disorder

Whereas meta-analytical data highlight abnormal frontocortical macrostructure (thickness/surface area/volume) in Major Depressive Disorder (MDD), the underlying microstructural processes remain uncharted, due to the use of conventional MRI scanners and acquisition techniques. We uniquely combined Ultra-High Field MRI at 7.0 Tesla with Quantitative Imaging to map intracortical myelin (proxied by longitudinal relaxation time T1) and iron concentration (proxied by transverse relaxation time T2*), microstructural processes deemed particularly germane to cortical macrostructure. Informed by meta-analytical evidence, we focused specifically on orbitofrontal and rostral anterior cingulate cortices among adult MDD patients (N = 48) and matched healthy controls (HC; N = 10). Analyses probed the association of MDD diagnosis and clinical profile (severity, medication use, comorbid anxiety disorders, childhood trauma) with aforementioned microstructural properties. MDD diagnosis (p’s < 0.05, Cohen’s D = 0.55–0.66) and symptom severity (p’s < 0.01, r = 0.271–0.267) both related to decreased intracortical myelination (higher T1 values) within the lateral orbitofrontal cortex, a region tightly coupled to processing negative affect and feelings of sadness in MDD. No relations were found with local iron concentrations. These findings allow uniquely fine-grained insights on frontocortical microstructure in MDD, and cautiously point to intracortical demyelination as a possible driver of macroscale cortical disintegrity in MDD.

Prospective Associations Between Personality Traits and Major Depressive Disorder Symptom Severity: The Mediating Role of Illness Representations.

Major depressive disorder (MDD) patients' personality traits and illness representations are linked to MDD severity. However, the associations between personality and illness representations in MDD and the mediating role of illness representations between personality and MDD severity have not been investigated. This study aimed to prospectively investigate the aforementioned associations and the possible mediating role of illness representations between personality and MDD severity. One hundred twenty-five patients with a MDD diagnosis, aged 48.18 ± 13.92 (84% females), participated in the study. Personality traits were measured with the Traits Personality Questionnaire at baseline. Illness representations were measured with the Illness Perception Questionnaire-Mental Health about five months later (mean = 5.08 ± 1.14 months). MDD severity was measured about 10 months after the baseline assessment (mean = 9.53 ± 2.36 months) with the Beck Depression Inventory. SPSS 29 and AMOS 27 were used to conduct correlational and parallel mediation analyses. According to the results, Neuroticism was positively and Extraversion was negatively linked to MDD severity. Negative MDD impact representations fully mediated these associations. Neuroticism and Extraversion are linked to future MDD severity through patients' representations of MDD's impact. Restructuring maladaptive representations about MDD's impact can be a promising way to reduce symptom severity in patients with high Neuroticism and low Extraversion levels.

Analysis of functional connectivity changes in attention networks and default mode networks in patients with depression and insomnia.

Major Depressive Disorder (MDD) and Insomnia Disorder (ID) are prevalent psychiatric conditions often occurring concurrently, leading to substantial impairment in daily functioning. Understanding the neurobiological underpinnings of these disorders and their comorbidity is crucial for developing effective interventions. This study aims to analyze changes in functional connectivity within attention networks and default mode networks in patients with depression and insomnia. The functional connectivity alterations in individuals with MDD, ID, comorbid MDD and insomnia (iMDD), and healthy controls (HC) were assessed from a cohort of 174 participants. They underwent rs-fMRI scans, demographic assessments, and scale evaluations for depression and sleep quality. Functional connectivity analysis was conducted using region-of-interest (ROI) and whole-brain methods. The MDD and iMDD groups exhibited higher Hamilton Depression Scale (HAMD) scores compared to HC and ID groups (P < 0.001). Both ID and MDD groups displayed enhanced connectivity between the left and right orbital frontal cortex compared to HC (P < 0.05), while the iMDD group showed reduced connectivity compared to HC and ID groups (P < 0.05). In the left insula, reduced connectivity with the right medial superior frontal gyrus was observed across patient groups compared to HC (P < 0.05), with the iMDD group showing increased connectivity compared to MDD (P < 0.05). Moreover, alterations in functional connectivity between the left thalamus and left temporal pole were found in iMDD compared to HC and MDD (P < 0.05). Correlation analyses revealed associations between abnormal connectivity and symptom severity in MDD and ID groups. Our findings demonstrate distinct patterns of altered functional connectivity in individuals with MDD, ID, and iMDD compared to healthy controls. These findings contribute to a better understanding of the pathophysiology of depression and insomnia, which could be used as a reference for the diagnosis and treatments of these patients.

Pharmacotherapy guideline concordance for major depressive disorder and its link to functioning via symptom change

Abstract Introduction: Alleviation of symptom severity for major depressive disorder (MDD) is known to be associated with a lagged improvement of functioning. Pharmacotherapy guidelines support algorithms for MDD treatment. However, it is currently unclear whether concordance with guidelines influences functional recovery. A guideline concordance algorithm (GCA-8) was used to measure this pathway in a naturalistic clinical setting. Methods: Data from 1403 adults (67% female, 84% non-Hispanic/Latino White, mean age of 43 years) with nonpsychotic MDD from the Penn State Psychiatry Clinical Assessment and Rating Evaluation System registry (visits from 02/01/2015 to 04/13/2021) were evaluated. Multivariable linear regression measured associations between GCA-8 and World Health Organization Disability Assessment Schedule 2.0 (WHODAS) scores. Mediation by MDD symptom severity using the Patient Health Questionnaire depression module (PHQ-9) was also evaluated. Results: This study found a statistically significant improvement in WHODAS scores (functioning) between baseline and final measures (−2 points, P &lt; .001) within one year. A one standard deviation increase in the GCA-8 score was associated with a 0.48-point reduction in mean disability score (total effect; P = .02) with significant mediation by the change in MDD symptom severity (coefficient = −0.51, P &lt; .001) and a nonsignificant natural direct effect of the GCA-8 independent of PHQ-9 change (coefficient = −0.02, P = .92). Conclusions: Higher pharmacotherapy guideline concordance is associated with better functioning for MDD patients; this association likely occurs through improvement in MDD symptom severity rather than directly.

Genome-wide transcriptomic and biochemical profiling of major depressive disorder: Unravelling association with susceptibility, severity, and antidepressant response

Identifying biomarkers for diagnosing Major Depressive Disorder (MDD), assessing its severity, and guiding treatment is crucial. We conducted whole genome transcriptomic study in North Indian population, and analyzed biochemical parameters. Our longitudinal study investigated gene-expression profiles from 72 drug-free MDD patients and 50 healthy controls(HCs) at baseline and 24 patients after 12-weeks of treatment. Gene expression analyses identified differentially expressed genes(DEGs) associated with MDD susceptibility, symptom severity and treatment response, independently validated by qPCR. Hierarchical clustering revealed distinct expression patterns between MDD and HCs, also between mild and severe cases. Enrichment analyses of significant DEGs revealed inflammatory, apoptosis, and immune-related pathways in MDD susceptibility, severity, and treatment response. Simultaneously, we assessed thirty biochemical parameters in the same cohort, showed significant differences between MDD and HCs in 13 parameters with monocytes, eosinophils, creatinine, SGPT, and total protein remained independent predictors of MDD in a multivariate-regression model. Our study supports the role of altered immune/inflammatory signaling in MDD pathophysiology, offering clinically relevant biochemical parameters and insights into transcriptomic gene regulation in MDD pathogenesis and treatment response.

Family Functioning, Illness-Related Self-Regulation Processes, and Clinical Outcomes in Major Depression: A Prospective Study in Greece.

Major depressive disorder (MDD) is a common, seriously impairing, and often recurrent mental disorder. Based on the predictions of the Circumplex Model of Marital and Family Systems and the Common-Sense Self-Regulation Model, the aim of the present prospective study is to examine the predictive value of clinical outcomes of a process model in which associations between perceived family functioning and patient's clinical outcomes (i.e., symptom severity and suicide risk) are mediated by illness representations and coping strategies. A total of 113 patients with a clinical diagnosis of MDD (16.8% males and 83.2% females) aged 47.25 ± 13.98 years and recruited from the outpatient department and the mobile mental health unit of the Psychiatric Clinic of the University Hospital of Heraklion in Crete, Greece, and from a Greek online depression peer-support group participated in the study. Family functioning was assessed in terms of cohesion and flexibility (Family Adaptability and Cohesion Evaluation Scales IV) at baseline. Illness representations (Illness Perception Questionnaire-Mental Health) and coping strategies (Brief Cope Orientation to Problems Experienced) were measured about five months later (5.04 ± 1.16 months). Symptom severity (Beck Depression Inventory) and suicidality (Risk Assessment Suicidality Scale) were measured about 10 months after the baseline assessment (9.56 ± 2.52 months). The results indicated that representations about MDD impact and symptom severity serially mediated the association between family cohesion and suicide risk in MDD. Furthermore, family cohesion was found to be linked with maladaptive coping through MDD impact representations. Family-based psychotherapeutic interventions specifically designed to target unhealthy family functioning, along with negative illness perceptions and dysfunctional coping, could be further developed and explored as adjunctive therapy to standard treatment in MDD.

Metacognition and Mentalization in Patients with Major Depressive Disorder

Social cognition is necessary to comprehend and interpret the behavioural intentions of oneself and others in social contexts. Despite an increasing understanding of social cognition deficits in mental illness, the relationship between Major Depressive Disorder (MDD) and high-order social cognition deficits (i.e., mentalization and metacognition) remains under-investigated. This paper aims to provide a holistic review of the existing empirical evidence on mentalization and metacognition in patients with MDD and suggest areas in need of further research. While a close relationship between MDD and metacognition has been consistently reported, some disagreement was raised regarding the association between mentalization capacity and MDD. Besides, the direction of the association between MDD, mentalization and metacognition was also underlined by studies examining the outcomes of high-order social cognition therapies. Mentalization and metacognition were both found to be predictors or at least moderators, of MDD diagnosis and symptom severity. Future evidence from developmental and neuroimaging studies may provide valuable insights into the field of study by uncovering the varying degrees of the impact caused by social cognition deficits and their associated neural mechanisms.

The clinical, economic, and patient-centric burden of insomnia symptom severity in adults with major depressive disorder in the United States.

Insomnia is prevalent in adults with major depressive disorder (MDD) and is a key diagnostic criterion of MDD; however, little is understood about the burden of insomnia symptom severity in MDD. We evaluated the relationship between insomnia symptom severity and the clinical, economic, and patient-centric burden among community-dwelling individuals with MDD. Respondents with diagnosed depression who reported insomnia symptoms in the past 12 months (N=4402) were identified from the 2019 United States National Health and Wellness Survey. Multivariable analyses assessed the association of Insomnia Severity Index (ISI) with health-related outcomes while controlling for sociodemographic and health characteristics. Further analyses also controlled for depression severity (9-item Patient Health Questionnaire). Mean ISI score was 14.3±5.6. Higher ISI was associated with greater depression severity (r=.51, p<.001). After adjustments, a one-standard deviation (5.6-point) increase in ISI score was significantly associated with higher depression (rate ratio [RR]=1.36), anxiety (RR=1.33) and daytime sleepiness (RR=1.16) levels, more healthcare provider (RR=1.13) and emergency room visits (RR=1.31), hospitalizations (RR=1.21), work productivity and activity impairment (RRs=1.27 and 1.23, respectively), and poorer mental and physical health-related quality of life (β=-3.853 and -1.999, respectively) (p<.001). These findings remained statistically significant when controlling for concurrent depression severity. In adults with MDD, greater insomnia symptom severity is associated with worse health-related outcomes, which suggests the importance of addressing insomnia symptoms as a clinical target for treating MDD.

Early maladaptive schema domains and suicide risk in major depressive disorder: the mediating role of patients’ illness-related self-regulation processes and symptom severity

AbstractEarly maladaptive schemas (EMS), illness representations, and coping are associated with clinical outcomes of patients with major depressive disorder (MDD). However, the pathways that link these factors are largely unknown. The present prospective study aimed at investigating the possible mediating role of illness representations and coping in the associations among schema domains, symptom severity, and suicide risk in MDD. Participants were 135 patients diagnosed with MDD, aged 48.13 ± 14.12 (84.4% females). The Young Schema Questionnaire-Short Form 3 was used to measure schema domains at baseline. Illness representations and coping were measured at approximately five months later (mean = 5.04 ± 1.16 months) with the Illness Perception Questionnaire-Mental Health and the Brief COPE Inventory, respectively. MDD outcomes were measured about 10 months after the baseline assessment (mean = 9.44 ± 2.36 months) with the Beck Depression Inventory and the Risk Assessment Suicidality Scale. SPSS AMOS 27 was used to conduct path analysis. Serial mediation Structural Equation Modelling, controlling for age, education, marital status, working status, MDD duration, pharmacotherapy, and psychotherapy, revealed that Impaired Autonomy and Performance was positively linked to suicide risk. Negative MDD impact representations and symptom severity serially mediated the aforementioned association. Finally, problem-focused coping was negatively related to symptom severity and suicide risk. This study’s main limitation was modest sample size. Representations regarding the impact and severity of MDD mediate the effects of Impaired Autonomy and Performance on future suicide risk in MDD. Healing Impaired Autonomy and Performance domain of EMS, restructuring patients’ representations of high MDD impact, and enhancing problem-focused coping could significantly reduce symptom severity and suicide risk in Schema Therapy with MDD individuals.

Exploring the role of serum uric acid as a biomarker in patients with schizophrenia, bipolar affective disorder, and major depressive disorder

BackgroundUric acid plays a pivotal role in the regulation of mood and behavior. The study aimed to elucidate the role of serum uric acid as a biomarker in patients with schizophrenia, bipolar affective disorder (BAD), and major depressive disorder (MDD) and to examine its relation to symptom domains and severity of illness.ResultsA total of 150 participants with schizophrenia, BAD, and MDD and 50 healthy controls were recruited. Patients were assessed using Structured Clinical Interview for DSM-IV Axis I Diagnosis (SCID-I), Positive and Negative Syndrome Scale (PANSS), the Young Mania Rating Scale (YMRS), and the Hamilton Depression Rating Scale (HAM-D). General Health Questionnaire (GHQ-28) was applied to healthy controls. Then, a blood draw from all participants was performed to measure serum uric acid level. According to this study, there was a statistically significant difference between patients with schizophrenia, BAD, MDD, and healthy controls, with regard to serum uric acid level (P = 0.007). On correlating symptom domains and severity of schizophrenia, bipolar, and MDD with serum uric acid level, there was only a statistically significant negative correlation between YMRS and serum uric acid level (P = 0.022).ConclusionsSerum uric acid could be a valuable biomarker in patients with schizophrenia, bipolar, and MDD especially in patients with bipolar disorder.

The mediating effect of stress reactivity in the 18-year bidirectional relationship between generalized anxiety and depression severity

BackgroundGeneralized anxiety disorder (GAD) and major depressive disorder (MDD) often precede and predict one another. Heightened stress reactivity may be a mediation mechanism underlying the long-term connections between GAD and MDD. However, cross-sectional studies on this topic have hindered directional inferences. MethodThe present study examined stress reactivity as a potential mediator of the sequential associations between GAD and MDD symptoms in a sample of 3,294 community-dwelling adults (M age = 45.6, range = 20–74). Participants completed three waves of measurement (T1, T2, and T3) spaced nine years apart. GAD and MDD symptom severity were assessed at T1, T2, and T3 (Composite International Diagnostic Interview-Short Form). Stress reactivity (Multidimensional Personality Questionnaire) was measured at T2. ResultsStructural equation mediation modeling demonstrated that higher T1 GAD symptoms positively predicted more severe T3 MDD symptoms via T2 stress reactivity, controlling for T1 MDD (d = 0.45–0.50). However, T2 stress reactivity was not a significant mediator in the relationship between T1 MDD severity and T3 GAD symptoms after controlling for T1 GAD. Direct effects indicated that T1 GAD positively predicted T3 MDD 18 years later and vice versa (d = 1.29–1.65). LimitationsStress reactivity was assessed using a self-report measure, limiting conclusions to perceived (vs. physiologically indexed) stress reactivity. ConclusionsThese findings indicate that stress reactivity may be one mechanism through which GAD leads to later MDD over prolonged durations. Overall, results suggest that targeting stress reactivity in treatments for GAD may reduce the risk of developing subsequent MDD.

Moral injury and chronic pain among military veterans in an integrated behavioral health clinic.

Military service may place veterans at increased risk for perpetrating, witnessing, or failing to prevent events that violate deeply held moral values. In some cases, veterans may develop moral injury (MI) symptoms that transcend and/or overlap with mental health conditions such as posttraumatic stress disorder (PTSD) and major depressive disorder (MDD). Further, PTSD and MDD are 2 established risk factors for chronic pain. However, research has not examined the association between MI symptoms and chronic pain. We tested whether MI would emerge as a salient correlate of concurrent reports of chronic pain in the presence of PTSD and MDD symptom severity among 59 veterans seeking integrated behavioral health care. Findings indicated the severity of MI symptoms was significantly linked with veterans' concurrent reports of chronic pain. Self-directed MI symptoms emerged as a correlate of worse pain in the presence of PTSD and MDD. Preliminary findings demonstrate possible associations between MI and chronic pain among veterans with a need for holistic health care. Future research should examine mechanisms for an apparent MI-chronic pain link. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

The unique association of posttraumatic stress disorder with hypertension among veterans: A replication of Kibler et al. (2009) using Bayesian estimation and data from the United States-Veteran Microbiome Project.

Kibler et al. (2009) reported that hypertension was related to PTSD independent of depression. These two conditions have significant diagnostic overlap. The present study sought to conceptually replicate this work with a veteran sample, using Bayesian estimation to directly update past results, as well as examine symptom severity scores in relation to hypertension. This was a secondary analysis of data obtained from the United States-Veteran Microbiome Project. Lifetime diagnoses of PTSD and major depressive disorder (MDD) were obtained from a structured clinical interview and hypertension diagnoses were extracted from electronic medical records. PTSD and depressive symptom severity were obtained from self-report measures. Logistic regressions with Bayesian estimation were used to estimate the associations between hypertension and (a) psychiatric diagnostic history and (b) symptom severity scores. Compared with veterans without lifetime diagnoses of either disorder, the PTSD-only group was estimated to have a 29% increase in hypertension risk, and the PTSD + MDD group was estimated to have a 66% increase in hypertension risk. Additionally, higher levels of PTSD symptom severity were associated with a higher risk of hypertension. PTSD diagnosis and symptom severity are uniquely associated with hypertension, independent of MDD or depressive symptom severity. These results support previous findings that PTSD might be a modifiable risk factor for the prevention and treatment of hypertension. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Classification of Major Depressive Disorder Based on Integrated Temporal and Spatial Functional MRI Variability Features of Dynamic Brain Network.

Characterization of the dynamics of functional brain network has gained increased attention in the study of depression. However, most studies have focused on single temporal dimension, while ignoring spatial dimensional information, hampering the discovery of validated biomarkers for depression. To integrate temporal and spatial functional MRI variability features of dynamic brain network in machine-learning techniques to distinguish patients with major depressive disorder (MDD) from healthy controls (HCs). Prospective. A discovery cohort including 119 patients and 106 HCs and an external validation cohort including 126 patients and 124 HCs from Rest-meta-MDD consortium. A 3.0 T/resting-state functional MRI using the gradient echo sequence. A random forest (RF) model integrating temporal and spatial variability features of dynamic brain networks with separate feature selection method (MSFS ) was implemented for MDD classification. Its performance was compared with three RF models that used: temporal variability features (MTVF ), spatial variability features (MSVF ), and integrated temporal and spatial variability features with hybrid feature selection method (MHFS ). A linear regression model based on MSFS was further established to assess MDD symptom severity, with prediction performance evaluated by the correlations between true and predicted scores. Receiver operating characteristic analyses with the area under the curve (AUC) were used to evaluate models' performance. Pearson's correlation was used to assess relationship of predicted scores and true scores. P < 0.05 was considered statistically significant. The model with MSFS achieved the best performance, with AUCs of 0.946 and 0.834 in the discovery and validation cohort, respectively. Additionally, altered temporal and spatial variability could significantly predict the severity of depression (r=0.640) and anxiety (r=0.616) in MDD. Integration of temporal and spatial variability features provides potential assistance for clinical diagnosis and symptom prediction of MDD. 2. Stage 2.

Study protocol for "MDMA-assisted therapy as a treatment for major depressive disorder: A proof of principle study".

Major depressive disorder (MDD) is a world-leading cause of disability. The available treatments are not effective in all patients, and there is a significant need for more effective treatment options. Here we present the protocol for an investigator-initiated and publicly funded trial of MDMA-assisted therapy (MDMA-AT) for MDD. This single-site, open-label study investigates the proof of principle and safety of MDMA-AT in participants with MDD and provides an initial impression of treatment effectiveness. A total of 12 participants [>18 years] with DSM-5 diagnosis of MDD will receive a flexible dose of MDMA in a therapeutic setting on two dosing days over a 4 week period preceded by three preparatory sessions. Each MDMA dosing session will be followed by three integration sessions. The primary outcome is change in MDD symptom severity, as measured by the mean change in MADRS scores from Baseline to 8 weeks after the second MDMA session. The secondary outcome is change in functional impairment, as evaluated by the mean change in Sheehan Disability Scale scores from Baseline to 8 weeks after the second MDMA session. Safety measures include vital signs, the incidence of Adverse Events and suicidality as measured by the Colombia-Suicide Severity Rating Scale. This proof of principle trial will inform the development of fully powered clinical trials, optimize the protocol for the administration of MDMA-AT in participants with MDD and explore uncertainties including barriers to recruitment, retention and acceptability of MDMA-AT as a treatment for MDD. EudraCT number 2021-000805-26.

Digital phenotyping of generalized anxiety disorder: using artificial intelligence to accurately predict symptom severity using wearable sensors in daily life

BackgroundGeneralized anxiety disorder (GAD) is a highly prevalent condition. Monitoring GAD symptoms requires substantial time, effort, and cost. The development of digital phenotypes of GAD may enable new scalable, timely, and inexpensive assessments of GAD symptoms.MethodThe current study used passive movement data collected within a large national cohort (N = 264) to assess GAD symptom severity.ResultsUsing one week of movement data, machine learning models accurately predicted GAD symptoms across a continuum (r = 0.511) and accurately detected those individuals with elevated GAD symptoms (AUC = 0.892, 70.0% Sensitivity, 95.5% Specificity, Brier Score = 0.092). Those with a risk score at the 90th percentile or above had 21 times the odds of having elevated GAD symptoms compared to those with lower risk scores. The risk score was most strongly associated with irritability, worry controllability, and restlessness (individual rs > 0.5). The risk scores for GAD were also discriminant of major depressive disorder symptom severity (r = 0.190).LimitationsThe current study examined the detection of GAD symptom severity rather than the prediction of GAD symptom severity across time. Furthermore, the instant sample of data did not include nighttime actigraphy, as participants were not asked to wear the actigraphs at night.ConclusionsThese results suggest that artificial intelligence can effectively utilize wearable movement data collected in daily life to accurately infer risk of GAD symptoms.

Decreased modular segregation of the frontal-parietal network in major depressive disorder.

Major depressive disorder (MDD) is a common psychiatric condition associated with aberrant large-scale distributed brain networks. However, it is unclear how the network dysfunction in MDD patients is characterized by imbalance or derangement of network modular segregation. Fifty-one MDD patients and forty-three matched healthy controls (HC) were recruited in the present study. We analyzed intrinsic brain activity derived from resting-state functional magnetic resonance imaging (R-fMRI) and then examined brain network segregation by computing the participation coefficient (PC). Further intra- and inter-modular connections analysis were preformed to explain atypical PC. Besides, we explored the potential relationship between the above graph theory measures and symptom severity in MDD. Lower modular segregation of the frontal–parietal network (FPN) was found in MDD compared with the HC group. The MDD group exhibited increased inter-module connections between the FPN and cingulo-opercular network (CON), between the FPN and cerebellum (Cere), between the CON and Cere. At the nodal level, the PC of the anterior prefrontal cortex, anterior cingulate cortex, inferior parietal lobule (IPL), and intraparietal sulcus showed larger in MDD. Additionally, the inter-module connections between the FPN and CON and the PC values of the IPL were negatively correlated with depression symptom in the MDD group. These findings might give evidence about abnormal FPN in MDD from the perspective of modular segregation in brain networks.

Anhedonia as a transdiagnostic symptom across psychological disorders: a network approach.

Anhedonia is apparent in different mental disorders and is suggested to be related to dysfunctions in the reward system and/or affect regulation. It may hence be a common underlying feature associated with symptom severity of mental disorders. We constructed a cross-sectional graphical Least Absolute Shrinkage and Selection Operator (LASSO) network and a relative importance network to estimate the relationships between anhedonia severity and the severity of symptom clusters of major depressive disorder (MDD), anxiety sensitivity (AS), attention-deficit hyperactivity disorder (ADHD), and autism spectrum disorder (ASD) in a sample of Dutch adult psychiatric patients (N = 557). Both these networks revealed anhedonia severity and depression symptom severity as central to the network. Results suggest that anhedonia severity may be predictive of the severity of symptom clusters of MDD, AS, ADHD, and ASD. MDD symptom severity may be predictive of AS and ADHD symptom severity. The results suggest that anhedonia may serve as a common underlying transdiagnostic psychopathology feature, predictive of the severity of symptom clusters of depression, AS, ADHD, and ASD. Thus, anhedonia may be associated with the high comorbidity between these symptom clusters and disorders. If our results will be replicated in future studies, it is recommended for clinicians to be more vigilant about screening for anhedonia and/or depression severity in individuals diagnosed with an anxiety disorder, ADHD and/or ASD.

The Association Between Home Stay and Symptom Severity in Major Depressive Disorder: Preliminary Findings From a Multicenter Observational Study Using Geolocation Data From Smartphones.

BackgroundMost smartphones and wearables are currently equipped with location sensing (using GPS and mobile network information), which enables continuous location tracking of their users. Several studies have reported that various mobility metrics, as well as home stay, that is, the amount of time an individual spends at home in a day, are associated with symptom severity in people with major depressive disorder (MDD). Owing to the use of small and homogeneous cohorts of participants, it is uncertain whether the findings reported in those studies generalize to a broader population of individuals with MDD symptoms.ObjectiveThe objective of this study is to examine the relationship between the overall severity of depressive symptoms, as assessed by the 8-item Patient Health Questionnaire, and median daily home stay over the 2 weeks preceding the completion of a questionnaire in individuals with MDD.MethodsWe used questionnaire and geolocation data of 164 participants with MDD collected in the observational Remote Assessment of Disease and Relapse–Major Depressive Disorder study. The participants were recruited from three study sites: King’s College London in the United Kingdom (109/164, 66.5%); Vrije Universiteit Medisch Centrum in Amsterdam, the Netherlands (17/164, 10.4%); and Centro de Investigación Biomédica en Red in Barcelona, Spain (38/164, 23.2%). We used a linear regression model and a resampling technique (n=100 draws) to investigate the relationship between home stay and the overall severity of MDD symptoms. Participant age at enrollment, gender, occupational status, and geolocation data quality metrics were included in the model as additional explanatory variables. The 95% 2-sided CIs were used to evaluate the significance of model variables.ResultsParticipant age and severity of MDD symptoms were found to be significantly related to home stay, with older (95% CI 0.161-0.325) and more severely affected individuals (95% CI 0.015-0.184) spending more time at home. The association between home stay and symptoms severity appeared to be stronger on weekdays (95% CI 0.023-0.178, median 0.098; home stay: 25th-75th percentiles 17.8-22.8, median 20.9 hours a day) than on weekends (95% CI −0.079 to 0.149, median 0.052; home stay: 25th-75th percentiles 19.7-23.5, median 22.3 hours a day). Furthermore, we found a significant modulation of home stay by occupational status, with employment reducing home stay (employed participants: 25th-75th percentiles 16.1-22.1, median 19.7 hours a day; unemployed participants: 25th-75th percentiles 20.4-23.5, median 22.6 hours a day).ConclusionsOur findings suggest that home stay is associated with symptom severity in MDD and demonstrate the importance of accounting for confounding factors in future studies. In addition, they illustrate that passive sensing of individuals with depression is feasible and could provide clinically relevant information to monitor the course of illness in patients with MDD.