Neurocognitive profiles of patients with first-episode and recurrent depression: a cross-sectional comparative study from China

Factors influencing the tendency of residual symptoms in patients with depressive disorders: a longitudinal study

BACKGROUND

Residual symptoms of depressive disorders are serious health problems. However, the progression process is hardly predictable due to high heterogeneity of the disease. This study aims to: (1) classify the patterns of changes in residual symptoms based on homogeneous data, and (2) identify potential predictors for these patterns.

METHODS

In this study, we conducted a data-driven Latent Class Growth Analysis (LCGA) to identify distinct tendencies of changes in residual symptoms, which were longitudinally quantified using the QIDS-SR16 at baseline and 1/3/6 months post-baseline for depressed patients. The association between baseline characteristics (e.g. clinical features and cognitive functions) and different progression tendencies were also identified.

RESULTS

The tendency of changes in residual symptoms was categorized into four classes: "light residual symptom decline (15.4%)", "residual symptom disappears (39.3%)", "steady residual symptom (6.3%)" and "severe residual symptom decline (39.0%)". We observed that the second class displayed more favorable recuperation outcomes than the rest of patients. The severity, recurrence, polypharmacy, and medication adherence of symptoms are intricately linked to the duration of residual symptoms' persistence. Additionally, clinical characteristics including sleep disturbances, depressive moods, alterations in appetite or weight, and difficulties with concentration have been identified as significant factors in the recovery process.

CONCLUSIONS

Our research findings indicate that certain clinical characteristics in patients with depressive disorders are associated with poor recovery from residual symptoms following acute treatment. This revelation holds significant value in the targeted attention to specific patients and the development of early intervention strategies for residual symptoms accordingly.

Physical and cognitive correlates, inflammatory levels, and treatment response in post-COVID-19 first-onset vs. recurrent depressive episodes

Psychiatric symptoms have been frequently reported in patients affected by COVID-19, both as new occurring and recurrences of pre-existing diseases. Depressive symptoms are estimated to affect at least 30% of patients following infection, with specific physical and cognitive features and relevant immune-inflammatory alterations. This study aimed to retrospectively characterize post-COVID-19 first-onset and recurrent major depressive episodes (MDE) and to evaluate the effects of antidepressants on physical and cognitive correlates of depression, in addition to mood, anxiety, and underlying inflammatory status. We evaluated 116 patients (44.8% males, 51.1 ± 17 years) with post-COVID-19 first-onset (38.8%) and recurrent (61.2%) MDE at baseline and after one- and three-month treatment with antidepressants (31% SSRIs, 25.9% SNRIs, 43.1% others). We assessed sociodemographic and clinical features and psychopathological dimensions through: Hamilton Depression and Anxiety Rating Scales; Short Form-36 Health Survey Questionnaire; Perceived Deficits Questionnaire-Depression 5-items. The systemic immune-inflammatory index was calculated to measure inflammation levels. Alongside the reduction of depression and anxiety (p < 0.001), physical and cognitive symptoms improved (p < 0.001) and inflammatory levels decreased (p < 0.001) throughout treatment in both groups. Post-COVID-19 recurrent MDE showed a significantly more severe course of physical and cognitive symptoms and persistently higher levels of inflammation than first-onset episodes. Antidepressants proved to be effective in both post-COVID-19 first-onset and recurrent MDE. However, a sustained inflammatory status might blunt treatment response in patients with recurrent depression in terms of physical correlates and cognition. Therefore, personalized approaches, possibly involving combinations with anti-inflammatory compounds, could promote better outcomes in this clinical population.

Processing speed and sustained attention in bipolar disorder and major depressive disorder: A systematic review and meta-analysis

OBJECTIVES

Cognitive impairment is a core feature of bipolar disorder (BD) and major depressive disorder (MDD). Deficits in processing speed (PS) and sustained attention (SA) may be particularly impaired and may underpin a broader profile of deficits, however current knowledge of the nature of these impairments is limited by heterogeneous results in the literature. Few reviews to date have attempted to disentangle sources of heterogeneity to assess the presence and magnitude of impairments in PS and SA in BD and MDD.

METHODS

One hundred and three studies were reviewed to examine performance in tests of PS and SA in BD (n = 3452) and MDD (n = 5461) compared to healthy controls (n = 8016). Neuropsychological methodology used in the literature was summarised. Data were meta-analysed to assess impairments in PS and SA for each neuropsychological test separately. Subgroup analysis was performed across mood states to investigate sources of heterogeneity.

RESULTS

Impairments were found across most neuropsychological tests, with small to large effect sizes for BD (range: d = 0.19-0.96) and MDD (range: d = 0.29-0.86). Impairments were present in symptomatic states and euthymia in most cases. Some outcome measures were not impaired in euthymia. Heterogeneity was observed for most neuropsychological tests and remained after separating by mood state. There inadequate data to meta-analyse some outcome measures, particularly for symptomatic groups.

CONCLUSION

Impairments in PS and SA in BD and MDD can be observed across most neuropsychological tests. Future research should further investigate the nature of these impairments across mood states, controlling for clinical confounds.

Cognitive performance in depression in low- and middle-income countries: A systematic review with meta-analytic components

BACKGROUND

Depression is highly prevalent in low- and middle- income countries (LMIC) and associated with significant cognitive dysfunction across multiple domains. However, little is known about neurocognitive tests used in people with depression in LMIC. We aimed to investigate cognitive performance and cognitive tests in depression research in LMIC.

METHODS

APA PsycInfo, Embase, Ovid MEDLINE, and Global Health were systematically searched for studies that implemented a cognitive performance test in a depressed, LMIC population. Tool quality was assessed using an adapted scale for quality of measures in cross-cultural settings. Data extracted included demographics, depression and cognitive performance measures, and cognitive performance comparisons between depression and control groups.

RESULTS

29 studies met eligibility criteria, involving a total of 19,100 participants from 11 LMIC. 93.1 % of studies were conducted in upper middle-income countries. 67 cognitive performance tools were implemented. Reliability was reported for 5.6 % of cognitive performance tests and validity was reported for 8.3 %. 36.1 % of tests used were culturally adapted. 75.9 % of included studies implemented at least one memory test. Cognitive deficits were observed in all depressed groups, especially in memory (Cohen's d = -1.60, 95 % CI -2.02 to -1.18).

LIMITATIONS

Heterogeneity between studies; averaged results across memory subtypes; no assessment of depression severity and cognitive deficits associations; restrictive search terms.

CONCLUSIONS

Cognitive impairments in depression, especially in memory, are prevalent in LMIC. This research has drawn attention to the burden of cognitive dysfunction in depression in LMIC, and to the disparate research gap in LMIC. PROSPERO registration CRD42022315397.

Changes of anhedonia and cognitive symptoms in first episode of depression and recurrent depression, an analysis of data from NSSD

BACKGROUND

Anhedonia and cognitive impairment are core features of major depressive disorder (MDD), and are essential to the treatment and prognosis. Here, we aimed to investigate anhedonia and its cognitive correlates between first episode of depression (FED) and recurrent depression (RD), which was part of the National Survey on Symptomatology of Depression.

METHODS

In this study, 1400 drug naïve FED patients and 487 on medicine RD patients were included. Differences of anhedonia, cognitive symptoms and other clinical characteristics between groups were compared via Student's t-test, or the chi-square test as appropriate. Partial correlation analysis was used to analyze the correlations between anhedonia and cognitive symptoms after adjusting for potential confounders. A stepwise logistic regression analysis was performed to identify relapse risk factors among symptomatic variables, demographic factors, clinical characteristics and medication use.

RESULTS

Compared to FED, RD patients displayed more comprehensive depressive, impaired cognitive and anhedonia symptoms. Cognitive symptoms were significantly related with the anhedonia symptoms with varying aspects. Patients taking emotional stabilizers displayed more abnormal cognitive symptoms, followed by benzodiazepines, and finally SSRIs, SNRIs and TCAs. The effect of drug use on anhedonia is not as extensive as that of cognitive symptoms.

CONCLUSION

Collectively, the results of this investigation advance the knowledge on changes in anhedonia and cognitive symptoms in MDD.

LIMITATIONS

As this is a cross sectional study, it is difficult to draw any causal conclusions between cognitive impairment and anhedonia in MDD, and to ascertain the worse cognitive performances identified here were induced by current drug use.

Altered spatio-temporal state patterns for functional dynamics estimation in first-episode drug-naive major depression

Patients with major depressive disorder (MDD) display affective and cognitive impairments. Although MDD-associated abnormalities of brain function and structure have been explored in depth, the relationships between MDD and spatio-temporal large-scale functional networks have not been evaluated in large-sample datasets. We employed data from International Big-Data Center for Depression Research (IBCDR), and comparable 543 healthy controls (HC) and 314 first-episode drug-naive (FEDN) MDD patients were included. We used a multivariate pattern classification method to learn informative spatio-temporal functional states. Brain states of each participant were extracted for functional dynamic estimation using an independent component analysis. Then, a multi-kernel pattern classification method was developed to identify discriminative spatio-temporal states associated with FEDN MDD. Finally, statistical analysis was applied to intrinsic and clinical brain characteristics. Compared with HC, FEDN MDD patients exhibited altered spatio-temporal functional states of the default mode network (DMN), the salience network, a hub network (centered on the dorsolateral prefrontal cortex), and a relatively complex coupling network (visual, DMN, motor-somatosensory and subcortical networks). Multi-kernel classification models to distinguish patients from HC obtained areas under the receiver operating characteristic curves up to 0.80. Classification scores correlated with Hamilton Depression Rating Scale scores and age at MDD onset. FEDN MDD patients had multiple abnormal spatio-temporal functional states. Classification scores derived from these states were related to symptom severity. The assessment of spatio-temporal states may represent a powerful clinical and research tool to distinguish between neuropsychiatric patients and controls.

Altered functional connectivity in first-episode and recurrent depression: A resting-state functional magnetic resonance imaging study

Background

Functional magnetic resonance imaging (fMRI) studies examining differences in the activity of brain networks between the first depressive episode (FDE) and recurrent depressive episode (RDE) are limited. The current study observed and compared the altered functional connectivity (FC) characteristics in the default mode network (DMN), cognitive control network (CCN), and affective network (AN) between the RDE and FDE. In addition, we further investigated the correlation between abnormal FC and clinical symptoms.

Methods

We recruited 32 patients with the RDE, 31 patients with the FDE, and 30 healthy controls (HCs). All subjects underwent resting-state fMRI. The seed-based FC method was used to analyze the abnormal brain networks in the DMN, CCN, and AN among the three groups and further explore the correlation between abnormal FC and clinical symptoms.

Results

One-way analysis of variance showed significant differences the FC in the DMN, CCN, and AN among the three groups in the frontal, parietal, temporal, and precuneus lobes and cerebellum. Compared with the RDE group, the FDE group generally showed reduced FC in the DMN, CCN, and AN. Compared with the HC group, the FDE group showed reduced FC in the DMN, CCN, and AN, while the RDE group showed reduced FC only in the DMN and AN. Moreover, the FC in the left posterior cingulate cortices and the right inferior temporal gyrus in the RDE group were positively correlated with the 17-item Hamilton Rating Scale for Depression (HAMD-17), and the FC in the left dorsolateral prefrontal cortices and the right precuneus in the FDE group were negatively correlated with the HAMD-17.

Conclusions

The RDE and FDE groups showed multiple abnormal brain networks. However, the alterations of abnormal FC were more extensive and intensive in the FDE group.