The relationship between personality traits and dysfunctional attitudes in individuals with or without major depressive disorder: a case control study.

BACKGROUND: Dysfunctional attitudes, which are characterized by distorted self-cognitions, were considered to be linked to personality traits. It was found that certain personality traits may predict dysfunctional attitudes in patients with major depressive disorder (MDD). Nonetheless, the relationship between personality traits and dysfunctional attitudes remains under-researched. AIMS: The aim of this study is to examine the relationship between specific domains of Sixteen Personality Factor (16PF) and dysfunctional attitudes in Chinese participants with or without MDD. In addition, the present study explores the associations between 16PF and eight subtypes of dysfunctional attitudes, based on the proposed eight-factor structure of the Chinese version of the Dysfunctional Attitude Scale-Form A (C-DAS-A). METHODS: One hundred and sixty-eight participants with MDD and 130 healthy participants were included in the study (Trial Registration Number: ChiCTR1800014591). Personality was assessed using the 16PF Questionnaire. Dysfunctional attitudes were measured through the C-DAS-A. RESULTS: The 16PF dimensions associated with dysfunctional attitudes and the eight subtypes were mainly concentrated in the four anxiety facets including factors C, L, O, and Q4, in both MDD and HC groups. There were significant differences in the 16 PF dimensions that would explain dysfunctional attitudes between the two groups, which were as follows: factors C, G, and O in the MDD group, and factors L and Q4 in the HC group. CONCLUSIONS: Personality traits, especially the anxiety-related personality traits, were distinctly associated with the development of dysfunctional attitudes in people with or without MDD.

The longitudinal change pattern of cognitive subtypes in medication-free patients with major depressive disorder: a cluster analysis.

This study aimed to investigate whether there are different cognitive subtypes in patients with major depressive disorder (MDD) and the change pattern of cognitive clusters across the course of MDD. A battery of comprehensive cognitive tests was used to assess the executive function, processing speed, attention, and memory of 153 medication-free patients and 142 healthy controls (HCs). After 6 months of treatment with antidepressants, 87 patients completed cognitive tests again. K-means cluster analysis was performed to determine the cognitive subtypes. A preserved cognition cluster and an impaired cognition cluster were identified in the acute episode phase and the 6-month follow-up phase. 80.5% of the patients remained in their original subgroup after 6 months of treatment. The impaired cognition cluster during the 6-month follow-up period could be predicted by impaired cognition during the episode phase, disease state (remission or non-remission), current illness duration, and education level. This study supporting the heterogeneity of cognitive performance across the course of disease in patients with MDD using cluster analysis. It was found that cognitive impairment during depressive episodes was predictive of poorer cognitive performance even after treatment with antidepressants. Therefore, interventions targeting cognitive function from the early stages of MDD is essential.

Impact of childhood maltreatment on adult resilience.

BACKGROUND: Previous studies suggested that childhood maltreatment is associated with poor health outcomes. While not everyone who experiences abuse as a child goes on to experience poor mental health, some traumatized people are grown to be more resilient than others. Few studies have examined the association between childhood maltreatment and adult resilience. This study aimed to determine different relationships between specific types and features of childhood maltreatment with adult resilience among Chinese with Major Depressive Disorder (MDD) and healthy controls (HCs). METHODS: A total of 101 patients with MDD and 116 participants in the healthy control (HC) group from Zhumadian Psychiatric Hospital and its nearby communities were included in this analysis. Childhood maltreatment was assessed retrospectively using Childhood Trauma Questionnaire (CTQ). Adults' resilience was assessed by the Connor-Davidson Resilience Scale (CD-RISC). Generalized linear models were applied between childhood maltreatment (specific types and features) and resilience adjusting for covariates. RESULTS: The total score of CD-RISC and factor scores of strength, optimism, and tenacity in the HC group were higher than those in the MDD group. CTQ total score had a negative association with optimism score among participants in MDD (ß=-0.087, P < 0.001) and HC (ß=-0.074, P = 0.023) groups. Higher emotional neglect (EN) score (ß=-0.169, P = 0.001) and physical neglect (PN) score (ß=-0.153, P = 0.043) were related to a worse optimism score in MDD group. Emotional abuse (EA) score was associated with a worse tenacity score (ß=-0.674, P = 0.031) in MDD group. For participants in HC group, higher EN and PN scores were related to worse resilience scores (tenacity, strength, and optimism). CONCLUSIONS: Patients with MDD showed lower optimism than HCs. Childhood maltreatment, especially childhood negect, independently contributed to optimism, with more severe childhood maltreatment predictive of worse performance of optimism. EA in childhood was also linked to worse tenacity in adult patients with MDD.

Mapping Neurophysiological Subtypes of Major Depressive Disorder Using Normative Models of the Functional Connectome.

BACKGROUND: Major depressive disorder (MDD) is a highly heterogeneous disorder that typically emerges in adolescence and can occur throughout adulthood. Studies aimed at quantitatively uncovering the heterogeneity of individual functional connectome abnormalities in MDD and identifying reproducibly distinct neurophysiological MDD subtypes across the lifespan, which could provide promising insights for precise diagnosis and treatment prediction, are still lacking. METHODS: Leveraging resting-state functional magnetic resonance imaging data from 1148 patients with MDD and 1079 healthy control participants (ages 11-93), we conducted the largest multisite analysis to date for neurophysiological MDD subtyping. First, we characterized typical lifespan trajectories of functional connectivity strength based on the normative model and quantitatively mapped the heterogeneous individual deviations among patients with MDD. Then, we identified neurobiological MDD subtypes using an unsupervised clustering algorithm and evaluated intersite reproducibility. Finally, we validated the subtype differences in baseline clinical variables and longitudinal treatment predictive capacity. RESULTS: Our findings indicated great intersubject heterogeneity in the spatial distribution and severity of functional connectome deviations among patients with MDD, which inspired the identification of 2 reproducible neurophysiological subtypes. Subtype 1 showed severe deviations, with positive deviations in the default mode, limbic, and subcortical areas and negative deviations in the sensorimotor and attention areas. Subtype 2 showed a moderate but converse deviation pattern. More importantly, subtype differences were observed in depressive item scores and the predictive ability of baseline deviations for antidepressant treatment outcomes. CONCLUSIONS: These findings shed light on our understanding of different neurobiological mechanisms underlying the clinical heterogeneity of MDD and are essential for developing personalized treatments for this disorder.

Aberrant Resting-State Functional Connectivity in MDD and the Antidepressant Treatment Effect-A 6-Month Follow-Up Study.

BACKGROUND: The mechanism by which antidepressants normalizing aberrant resting-state functional connectivity (rsFC) in patients with major depressive disorder (MDD) is still a matter of debate. The current study aimed to investigate aberrant rsFC and whether antidepressants would restore the aberrant rsFC in patients with MDD. METHODS: A total of 196 patients with MDD and 143 healthy controls (HCs) received the resting-state functional magnetic resonance imaging and clinical assessments at baseline. Patients with MDD received antidepressant treatment after baseline assessment and were re-scanned at the 6-month follow-up. Network-based statistics were employed to identify aberrant rsFC and rsFC changes in patients with MDD and to compare the rsFC differences between remitters and non-remitters. RESULTS: We identified a significantly decreased sub-network and a significantly increased sub-network in MDD at baseline. Approximately half of the aberrant rsFC remained significantly different from HCs after 6-month treatment. Significant overlaps were found between baseline reduced sub-network and follow-up increased sub-network, and between baseline increased sub-network and follow-up decreased sub-network. Besides, rsFC at baseline and rsFC changes between baseline and follow-up in remitters were not different from non-remitters. CONCLUSIONS: Most aberrant rsFC in patients with MDD showed state-independence. Although antidepressants may modulate aberrant rsFC, they may not specifically target these aberrations to achieve therapeutic effects, with only a few having been directly linked to treatment efficacy.

The percentage of cognitive impairment in patients with major depressive disorder over the course of the depression: A longitudinal study.

BACKGROUND: Cognitive impairments (CI) are prevalent and persistent in patients with major depressive disorder (MDD). There is a lack of longitudinal studies exploring the changes of the percentage of CI among MDD patients before and after a long-term antidepressant treatment and the risk factors that predict the residual CI. METHODS: A neurocognitive battery was performed to assess four domains of cognitive function, including executive function, processing speed, attention, and memory. CI was set as cognitive performance scoring 1.5 SDs lower than the mean scores of healthy controls (HCs). Logistic regression models were conducted to examine the risk factors for the after-treatment residual CI. RESULTS: Over 50 % of patients showed at least one kind of CI. After the antidepressant treatment, the overall cognitive performance among remitted MDD patients was identical to HCs, however, there were still 24 % of the remitted MDD patients had at least one type of CI, especially in executive function and attention. Additionally, the percentage of CI among non-remitted MDD patients was still significantly different from HCs. Our regression analysis further identified that except for the non-remission of MDD, CI at baseline could also predict the residual CI in MDD patients. LIMITATIONS: A relatively high drop-out rate at follow-ups. CONCLUSIONS: Cognitive impairment in executive function and attention is persistent even in remitted patients with MDD, and baseline cognitive performance can predict the post-treatment cognitive performance. Our findings emphasize the integral role of early cognitive intervention in MDD treatment.

Relationship between childhood maltreatment and cognitive function in medication-free patients with major depressive disorder.

This study aimed to elucidate the contribution of childhood maltreatment (CM) and the disease of major depressive disorder (MDD) on cognitive function in medication-free patients in a current depressive episode, and to examine the effect of CM on the improvement of cognitive function after treatment with antidepressants. One hundred and fifty-three unmedicated patients with MDD and 142 healthy controls (HCs) underwent clinical interviews. CM assessment was performed using the Childhood Trauma Questionnaire (CTQ), and a battery of comprehensive neurocognitive tests was used to assess the participants' executive function, processing speed, attention, and memory. After 6 months of treatment with antidepressants, the neurocognitive tests were reperformed in patients with MDD and HCs. There was a significant main effect of MDD on all four cognitive domains, while the main effect of CM was only significant on memory. No significant interactive effect was found between MDD and CM on any of the cognitive domains. In the MDD group, higher CTQ total score was predictive of poorer memory performance. After treatment, significant main effects of treatment and MDD were found on all four cognitive domains in remitted patients with MDD. No significant main effect of CM or three-way interaction effect of treatment × MDD × CM was found on any of the cognitive domains. The disease of MDD contributed to impairments in all four cognitive domains. CM independently contributed to memory impairment in patients in a current depressive episode, with higher severity of CM predictive of poorer memory performance.

Modulation of resting-state functional connectivity in default mode network is associated with the long-term treatment outcome in major depressive disorder.

BACKGROUND: Treatment non-response and recurrence are the main sources of disease burden in major depressive disorder (MDD). However, little is known about its neurobiological mechanism concerning the brain network changes accompanying pharmacotherapy. The present study investigated the changes in the intrinsic brain networks during 6-month antidepressant treatment phase associated with the treatment response and recurrence in MDD. METHODS: Resting-state functional magnetic resonance imaging was acquired from untreated patients with MDD and healthy controls at baseline. The patients' depressive symptoms were monitored by using the Hamilton Rating Scale for Depression (HAMD). After 6 months of antidepressant treatment, patients were re-scanned and followed up every 6 months over 2 years. Traditional statistical analysis as well as machine learning approaches were conducted to investigate the longitudinal changes in macro-scale resting-state functional network connectivity (rsFNC) strength and micro-scale resting-state functional connectivity (rsFC) associated with long-term treatment outcome in MDD. RESULTS: Repeated measures of the general linear model demonstrated a significant difference in the default mode network (DMN) rsFNC change before and after the 6-month antidepressant treatment between remitters and non-remitters. The difference in the rsFNC change over the 6-month antidepressant treatment between recurring and stable MDD was also specific to DMN. Machine learning analysis results revealed that only the DMN rsFC change successfully distinguished non-remitters from the remitters at 6 months and recurring from stable MDD during the 2-year follow-up. CONCLUSION: Our findings demonstrated that the intrinsic DMN connectivity could be a unique and important target for treatment and recurrence prevention in MDD.

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OBJECTIVES: Major depressive disorder (MDD) patients with anhedonia tend to have a poor prognosis. The underlying imaging basis for anhedonia in MDD remains largely unknown. The relationship between nodal properties and anhedonia in MDD patients need to be further investigated. Herein, this study aims to explore differences of cerebral functional node characteristics in MDD patients with severe anhedonia (MDD-SA) and MDD patients with mild anhedonia (MDD-MA) before and after the antidepressant treatment. METHODS: Ninety participants with current MDD were recruited in this study. 24-Item Hamilton Depression Scale (HAMD-24) and Snaith-Hamilton Pleasure Scale (SHAPS) were used to assess the severity of depression and anhedonia at baseline and the end of 6-months treatment. The MDD patients who scored above the 25th percentile on the SHAPS were assigned to an MDD-SA group (n=19), while those who scored below the 25th percentile were assigned to an MDD-MA group (n=18). All patients in the 2 groups received antidepressant treatment. Functional magnetic resonance imaging (fMRI) images of all the patients were collected at baseline and the end of 6-months treatment. Graph theory was applied to analyze the patients' cerebral functional nodal characteristics, which were measured by efficiency (ei) and degree (ki). RESULTS: Repeated measures 2-factor ANCOVA showed significant main effects on group on the ei and ki values of left superior frontal gyrus (LSFG) (P=0.003 and P=0.008, respectively), and on the ei and ki values of left medial orbital-frontal gyrus (LMOFG) (P=0.004 and P=0.008, respectively). Compared with the MDD-MA group, the significantly higher ei and ki values of the LSFG (P=0.015 and P=0.021, respectively), and the significantly higher ei and ki values of the LMOFG (P=0.015 and P=0.037, respectively) were observed in the MDD-SA group at baseline. Meanwhile, higher SHAPS scores could result in higher ei and ki values of LSFG (P=0.019 and P=0.026, respectively), and higher ei value of LMOFG (P=0.040) at baseline; higher SHAPS scores could result in higher ei values of LSFG (P=0.049) at the end of 6-months treatment. The multiple linear regression analysis revealed that sex were negatively correlated with the ei and ki values of LSFG (r= -0.014, P=0.004; r=-1.153, P=0.001, respectively). The onset age of MDD was negatively correlated with the ki value of LSFG (r=-0.420, P=0.034) at the end of 6-months treatment. We also found that SHAPS scores at baseline were positively correlated with the HAMD-24 scores (r=0.387, P=0.022) at the end of 6-months treatment. CONCLUSIONS: There are obvious differences in nodal properties between the MDD-SA and the MDD-MA patients, such as the high ei of LSFG in the MDD-SA patients, which may be associated with the severity of anhedonia. These nodal properties could be potential biomarkers for the prognosis of MDD. The increased ei and ki values in the LSFG of MDD-SA patients may underlie a compensatory mechanism or protective mechanism. The mechanism may be an important component of the pathological mechanism of MDD-SA. The poor prognosis in the MDD-SA patients suggests that anhedonia may predict a worse prognosis in MDD patients. Sex and onset age of MDD may affect the nodal properties of LSFG at baseline and the end of 6-months treatment.

Childhood Emotional Neglect Is Associated With Low Social Support in Chinese Patients With Major Depressive Disorder.

Background: Previous studies have shown that childhood maltreatment (CM) is closely associated with social support in the general population. However, little is known about the associations of different types of CM with social support in Chinese patients with major depressive disorder (MDD), which was the goal of the current study. Methods: One hundred and sixty-six patients with moderate-to-severe MDD were enrolled. Participants were assessed by the Childhood Trauma Questionnaire-28 item Short Form, Social Support Rating Scale (SSRS), the 24-item Hamilton rating scale for depression, and the 14-item Hamilton Anxiety Rating Scale. Correlation analysis and Hierarchical multiple linear regression analysis were adopted to investigate associations of types of CM with social support. Results: (1) Physical neglect (PN) and emotional neglect (EN) were the most commonly reported types of CM in patients with MDD. (2) EN was the only type of CM significant in the regression models of the SSRS total score, the score of subjective support, and the score of utilization of support. Limitations: The data of CM was collected retrospectively and recall bias may be introduced. Assessment of CM and social support were self-reported and could be influenced by the depression status. Conclusion: In Chinese patients with MDD, PN and EN are the most prevalent types of CM. EN is the only type of CM associated with low social support in regression models, calling for special attention in the assessment and intervention of EN.

Childhood Maltreatment Predicts Specific Types of Dysfunctional Attitudes in Participants With and Without Depression.

Background: Studies have shown a strong association between childhood maltreatment (CM) and major depressive disorder (MDD). Dysfunctional attitudes (DAs) play a crucial role in the development of MDD. In this study, we aimed to investigate whether (1) DAs are associated with CM, (2) specific CM types predict specific types of DAs, and (3) higher childhood trauma counts (CTCs) predict more DAs. Methods: One hundred seventy-one MDD participants and 156 healthy controls (HCs) were enrolled for the study. CM was assessed retrospectively with the Childhood Trauma Questionnaire. DAs were evaluated using the Chinese version of the Dysfunctional Attitude Scale-Form A (C-DAS-A). A series of analyses, including multiple analyses of covariance and hierarchical regression analyses, were used in this study to examine the hypotheses. Results: The proportion of CM was 60.2% in the MDD group and 44.2% in the HC group. The 2 × 2 analysis of covariance results showed no interaction effect between CM and MDD on C-DAS-A total score. When the factor scores replaced the C-DAS-A total score, a similar trend was observed. Within the MDD group, emotional abuse (EA) predicted two forms of DAs: self-determination type and overall DAs; physical neglect (PN) was predictive of attraction and repulsion-type DAs. Higher childhood trauma counts significantly predicted more types of DAs in the MDD group. Conclusion: DAs are a trait feature of CM. EA and PN predict specific types of DAs in MDD patients. Higher CTCs predict more DAs in MDD patients.

Functional connectivity evidence for state-independent executive function deficits in patients with major depressive disorder.

BACKGROUND: Persistent neurocognitive deficits are often associated with poor outcomes of major depressive disorder (MDD). Executive dysfunction is the most common cognitive deficit in MDD. However, it remains unclear which subcomponent of executive dysfunction is state-independent with distinct neural substrates. METHODS: A comprehensive neurocognitive test battery was used to assess four subcomponents of executive function (working memory, inhibition, shifting, and verbal fluency) in 95 MDD patients and 111 matched healthy controls (HCs). After 6 months of paroxetine treatment, 56 patients achieved clinical remission (rMDD) and completed the second-time neurocognitive test. Network-based statistics analysis was utilized to explore the changes in functional connectivity (FC). RESULTS: Compared with the HCs, all the four subcomponents of MDD patients were significantly impaired. After treatment, there was a significant improvement in working memory, inhibition, and verbal fluency in the rMDD group. And shifting and verbal fluency of the rMDD group remained impaired compared with the HCs. Fifteen functional connections were interrupted in the MDD group, and 11 connections remained in a disrupted state after treatment. Importantly, verbal fluency was negatively correlated with the disrupted FC between the right dorsal prefrontal cortex and the left inferior parietal lobule in patients with MDD and remitted MDD. LIMITATIONS: The correlation analysis of the association between cognitive impairment and connectivity alterations precluded us from making causal inferences. CONCLUSIONS: Verbal fluency is the potential state-independent cognitive deficit with distinct neural basis in patients with MDD.

Evidence for Progressive Cognitive Deficits in Patients With Major Depressive Disorder.

Background: Cognitive deficits have shown progressive feature in major depressive disorder (MDD). However, it remains unknown which component of cognitive function is progressively impaired across episodes of MDD. Here we aim to identify the progressively impaired cognitive components in patients with MDD. Methods: A comprehensive neurocognitive test battery was used to assess the cognitive components (executive function, attention, processing speed, memory, working memory, inhibition, shifting, and verbal fluency) in 35 patients with first-episode MDD (FED), 60 patients with recurrent MDD (RD) and 111 matched healthy controls (HCs). After 6 months of treatment with antidepressant, 20 FED and 36 RD patients achieved clinical remission and completed their second-time neurocognitive tests. Statistical analyses were conducted to identify the impaired cognitive components in the FED and RD groups before and after treatment, and to assess the relationship between the cognitive components and the number of episodes and total illness duration in the MDD patient group. Results: At baseline, both the FED and RD groups showed impairments in all of the cognitive components; the FED and RD groups showed no significant difference in all of the components except for shifting. After remission, only shifting in the RD group showed no significant improvement and remained in an impaired status. Furthermore, shifting was the only component negatively correlated with the number of episodes as well as the total illness duration. Conclusions: Shifting may serve as the progressive cognitive deficit across episodes of MDD. Clinical Trials Registration: Registry name: HPA function and MRI study of trauma-related depression; Registration number: ChiCTR1800014591; URL: http://www.chictr.org.cn/edit.aspx?pid=24669&htm=4.

The neuroprogressive nature of major depressive disorder: evidence from an intrinsic connectome analysis.

Major depressive disorder (MDD) is a prevailing chronic mental disorder with lifetime recurring episodes. Recurrent depression (RD) has been reported to be associated with greater severity of depression, higher relapse rate and prominent functioning impairments than first-episode depression (FED), suggesting the progressive nature of depression. However, there is still little evidence regarding brain functional connectome. In this study, 95 medication-free MDD patients (35 with FED and 60 with RD) and 111 matched healthy controls (HCs) underwent resting-state functional magnetic resonance imaging (fMRI) scanning. After six months of treatment with paroxetine, 56 patients achieved clinical remission and finished their second scan. Network-based statistics analysis was used to explore the changes in functional connectivity. The results revealed that, compared with HCs, patients with FED exhibited hypoconnectivity in the somatomotor, default mode and dorsal attention networks, and RD exhibited hyperconnectivity in the somatomotor, salience, executive control, default mode and dorsal attention networks, as well as within and between salience and executive control networks. Moreover, the disrupted components in patients with current MDD did not change significantly when the patients achieved remission after treatment, and sub-hyperconnectivity and sub-hypoconnectivity were still found in those with remitted RD. Additionally, the hypoconnectivity in FED and hyperconnectivity in RD were associated with the number of episodes and total illness duration. This study provides initial evidence supporting that impairment of intrinsic functional connectivity across the course of depression is a progressive process.

State-Independent and -Dependent Structural Connectivity Alterations in Depression.

Some brain abnormalities persist at the remission phase, that is, the state-independent abnormalities, which may be one of the reasons for the high recurrence of major depressive disorder (MDD). Hence, it is of great significance to identify state-independent abnormalities of MDD through longitudinal investigation. Ninety-nine MDD patients and 118 healthy controls (HCs) received diffusion tensor imaging scanning at baseline. After 6-month antidepressant treatment, 68 patients received a second scan, among which 59 patients achieved full clinical remission. Differences in whole-brain structural connectivity (SC) between patients with MDD at baseline and HCs were estimated by two-sample t-tests. Masked with significantly changed SCs in MDD, two-sample t-tests were conducted between the remitted MDD subgroup at follow-up and HCs, and paired t-tests were implemented to compare the differences of SC in the remitted MDD subgroup before and after treatment. Significantly decreased SC between the right insula and the anterior temporal cortex (ATC), between the right ATC and the posterior temporal cortex (PTC), between the left ATC and the auditory cortex as well as increased connectivity between the right posterior cingulate cortex (PCC) and the left medial parietal cortex (MPC) were observed in the MDD group compared with the HC group at baseline (p < 0.05, FDR corrected). The decreased connectivity between the right insula and the ATC and increased connectivity between the right PCC and the left MPC persisted in the remitted MDD subgroup at follow-up (p < 0.05, FDR corrected). The decreased SC between the right insula and the ATC and increased SC between the right PCC and left MPC showed state-independent characters, which may be implicated in the sustained negative attention bias and motor retardation in MDD. In contrast, the decreased SC between the right ATC and the PTC and between the left ATC and the auditory cortex seemed to be state-dependent.

Corrigendum: Gender Differences in Dysfunctional Attitudes in Major Depressive Disorder.

[This corrects the article DOI: 10.3389/fpsyt.2020.00086.].

The effects of childhood trauma on the onset, severity and improvement of depression: The role of dysfunctional attitudes and cortisol levels.

BACKGROUND: Childhood trauma is an important early social risk factor for the development of the major depressive disorder (MDD). Both childhood trauma and depression are associated with dysfunctional attitudes and dysregulation in stress hormones. We aimed to clarify the path from childhood trauma to depression and identify potential predictors of antidepressant treatment outcomes. OBJECTIVES: One hundred and thirty-nine MDD patients and 112 healthy controls were included at baseline. Depressive symptoms were assessed with both self-reported and expert-rated scales. Childhood trauma and dysfunctional attitudes were evaluated and blood cortisol levels were assayed. Patients received an open-label antidepressant trial with paroxetine and their depressive symptoms were monitored by the Hamilton Depression Rating Scale (HAMD) during 6 months of treatment. After 6 months, 94 patients received the same assessments as the baseline. RESULTS: At baseline, the influence of childhood trauma on depression diagnosis was mediated by dysfunctional attitudes. In patients with MDD, the influence of childhood trauma on depression severity was mediated by both dysfunctional attitudes and cortisol levels. Baseline childhood trauma predicted the antidepressant treatment outcome during early treatment phase and baseline cortisol levels predicted the antidepressant treatment outcome at later treatment phase. After 6-month antidepressant treatment, a significant remission by time effect was found on dysfunctional attitudes and depression severity but not on cortisol levels. CONCLUSION: Effect of childhood trauma on depression onset was mediated by dysfunctional attitudes. The relationship between childhood trauma and depressive symptoms was mediated by dysfunctional attitudes and cortisol levels in MDD patients. Baseline childhood trauma and cortisol levels may be moderators for antidepressant treatment response at different treatment phase.

Longitudinal changes of amplitude of low-frequency fluctuations in MDD patients: A 6-month follow-up resting-state functional magnetic resonance imaging study.

OBJECTIVE: The aim of this study includes: (1) using resting-state functional magnetic resonance imaging (rsfMRI) to explore the aberrant brain regional spontaneous brain activities in acute major depressive disorder (MDD) patients; (2) to determine whether the abnormalities could be restored after 6 months of antidepressant treatment; (3) to investigate whether the differences in regional spontaneous brain activities are associated with clinical variables in MDD. METHOD: RsfMRI scanning was performed in 149 MDD patients and 122 healthy control (HC) subjects at baseline. After 6 months of antidepressant treatment, rsfMRI scanning was reperformed in remitted MDD patients (MDD-R) (n=63). The characteristics of the amplitude of low-frequency fluctuations (ALFF), and the relationship between the fMRI representatives and clinical variables in the MDD group were analyzed. RESULTS: (1) Compared to healthy controls, significantly decreased ALFF in the right precuneus/posterior cingulate cortex (PCUN/PCC) was detected in MDD. (2) The ALFF value of precuneus in MDD-R group did not change significantly after a 6-month antidepressant treatment and was still lower than the HC group when remission was achieved (P = 0.002). (3) No correlations were found between ALFF in the right PCUN/PCC and Hamilton Depression Rating Scale(HAMD) total score, illness duration, age of onset, and the number of episodes in the baseline MDD group. The ALFF change was not correlated with depressive symptom improvement in MDD-R group. CONCLUSIONS: The reduction of ALFF in the precuneus persisted in MDD who achieved clinical remission, suggesting that the decreased ALFF in PCUN/PCC may be a trait marker of MDD.

State-Dependent and Trait-Like Characteristics of Dysfunctional Attitudes in Patients With Major Depressive Disorder.

BACKGROUND: Studies have shown that patients with major depressive disorder (MDD) exhibit elevated dysfunctional attitudes (DAs). However, it remains controversial whether the DAs are state-dependent or trait-like features of MDD. METHODS: This study recruited 172 patients and 159 healthy controls (HCs) at baseline. DAs were respectively assessed by the 24-item Hamilton Depression Rating Scale (HAMD24) and the Chinese version of Dysfunctional Attitude Scale form A (C-DAS-A). After baseline, patients received a 6-month antidepressant treatment. General linear models were used to analyze the differences in the C-DAS-A total and factor scores between the acute and remitted MDD groups and the HC group. Paired t tests were used to assess the changes of C-DAS-A total and factor scores in the remitted MDD group before and after treatment. RESULTS: At baseline, patients with MDD showed significantly higher scores in C-DAS-A and its subscales than HCs (all P < 0.05). After treatment, the C-DAS-A total and factor scores decreased significantly in the remitted MDD group (all P < 0.05). However, the C-DAS-A total (P = 0.005) and five factors' scores (vulnerability, attraction and repulsion, perfectionism, compulsion, and dependence) remained elevated in the remitted MDD group as compared with HCs (all P < 0.05). There were moderate correlations between the baseline and remission phase C-DAS-A total and five factors' scores (all P < 0.05). CONCLUSION: DAs show a mixture of state-dependent and trait-like characteristics in MDD with partial improvement in the remission phase. Special attention should be paid to the residual DAs in the remitted MDD for the prevention of relapse.

Connectome-based models can predict early symptom improvement in major depressive disorder.

BACKGROUND: Major depressive disorder (MDD) is a debilitating mental illness with more than 50% of patients not achieving an adequate response using first-line treatments. Reliable models that predict antidepressant treatment outcome are needed to guide clinical decision making. We aimed to build predictive models of treatment improvement for MDD patients using machine learning approaches based on fMRI resting-state functional connectivity patterns. METHODS: Resting-state fMRI data were acquired from 192 untreated MDD patients at recruitment, and their severity of depression was assessed by Hamilton Rating Scale for Depression (HAMD) at baseline. Patients were given medication after the initial MR scan and their symptoms were monitored through HAMD for a period of six months. Connectome-based predictive modeling (CPM) algorithms were implemented to predict the improvement in HAMD score at one month from resting-state connectivity at baseline. Additionally, by selectively combining the features from all leave-one-out iterations in the model building stage, we created a consensus model that could be generalized to predict improvement in HAMD score in samples of non-overlapping subjects at different time points. RESULTS: Using baseline functional connectivity, CPM successfully predicted symptom improvement of depression at one month. In addition, a consensus 'MDD improvement model' could predict symptom improvement for novel individuals at the two-week, one-month, two-month and three-month time points after antidepressant treatment. CONCLUSIONS: Individual pre-treatment functional brain networks contain meaningful information that can be gleaned to build predictors of treatment outcome. The identified MDD improvement networks could be an appropriate biomarker for predicting individual therapeutic response of antidepressant treatment. Replication and validation using other large datasets will be a key next step before these models can be used in clinical practice.