Prevalence of depressive disorder in the adult population of Latin America: a systematic review and meta-analysis.

Background: Depressive disorder is one of the leading causes of disability worldwide; however its prevalence and association with inequality and crime is poorly characterised in Latin America. This study aimed to: i. systematically review population-based studies of prevalence of ICD/DSM depressive disorder in Latin America, ii. report pooled regional, country, and sex-specific prevalence estimates, and iii. test its association with four country-level development indicators: human development (HDI), income (Gini) and gender inequality (GII), and intentional homicide rate (IHR). Methods: We conducted a systematic review and meta-analysis of population-based studies reporting primary data on the prevalence of ICD/DSM depressive disorder in Latin America from 1990 to 2023, irrespective of language. We searched PubMed, PsycINFO, Cochrane Library, SciELO (regional database), LILAC (regional database), and available grey literature. Study quality was assessed using JBI's critical appraisal tools. We generated pooled estimates using random-effects meta-analysis; heterogeneity was assessed using the I2 statistic. Meta-regression analyses were used to test associations of depression prevalence with indicators of inequality and human development. The study was registered with PROSPERO (CRD42019143054). Findings: Using data from 40 studies in Latin America, lifetime, 12-month, and current prevalence of ICD/DSM depressive disorder were calculated at 12.58% (95% CI 11.00%-14.16%); 5.30% (4.55-6.06%), and 3.12% (2.22-4.03), respectively. Heterogeneity was high across lifetime, 12-month, and current prevalence, sex, and countries. 12-month and current prevalence was associated with higher Gini and GII, 12-month prevalence with lower HDI, and current prevalence with higher IHR. Interpretation: We found a high prevalence of ICD/DSM depressive disorders in Latin America, and a statistically significant association with inequality and development indicators. The high heterogeneity found across prevalence periods and the major gaps in country representation underscore the need to escalate efforts to improve mental health access and research capabilities in Latin America. Systematic, comparable prevalence estimates would inform more effective decision-making in the region. Funding: Pfizer Independent Medical Education Grant.

Reduced resilience of brain state transitions in anti-N-methyl-D-aspartate receptor encephalitis.

Patients with anti-N-methyl-aspartate receptor (NMDA) receptor encephalitis suffer from a severe neuropsychiatric syndrome, yet most patients show no abnormalities in routine magnetic resonance imaging. In contrast, advanced neuroimaging studies have consistently identified disrupted functional connectivity in these patients, with recent work suggesting increased volatility of functional state dynamics. Here, we investigate these network dynamics through the spatiotemporal trajectory of meta-state transitions, yielding a time-resolved account of brain state exploration in anti-NMDA receptor encephalitis. To this end, resting-state functional magnetic resonance imaging data were acquired in 73 patients with anti-NMDA receptor encephalitis and 73 age- and sex-matched healthy controls. Time-resolved functional connectivity was clustered into brain meta-states, giving rise to a time-resolved transition network graph with states as nodes and transitions between brain meta-states as weighted, directed edges. Network topology, robustness and transition cost of these transition networks were compared between groups. Transition networks of patients showed significantly lower local efficiency (t = -2.41, pFDR  = .029), lower robustness (t = -2.01, pFDR  = .048) and higher leap size (t = 2.18, pFDR  = .037) compared with controls. Furthermore, the ratio of within-to-between module transitions and state similarity was significantly lower in patients. Importantly, alterations of brain state transitions correlated with disease severity. Together, these findings reveal systematic alterations of transition networks in patients, suggesting that anti-NMDA receptor encephalitis is characterized by reduced stability of brain state transitions and that this reduced resilience of transition networks plays a clinically relevant role in the manifestation of the disease.

Dysconnectivity in Schizophrenia Revisited: Abnormal Temporal Organization of Dynamic Functional Connectivity in Patients With a First Episode of Psychosis.

BACKGROUND AND HYPOTHESIS: Abnormal functional connectivity between brain regions is a consistent finding in schizophrenia, including functional magnetic resonance imaging (fMRI) studies. Recent studies have highlighted that connectivity changes in time in healthy subjects. We here examined the temporal changes in functional connectivity in patients with a first episode of psychosis (FEP). Specifically, we analyzed the temporal order in which whole-brain organization states were visited. STUDY DESIGN: Two case-control studies, including in each sample a subgroup scanned a second time after treatment. Chilean sample included 79 patients with a FEP and 83 healthy controls. Mexican sample included 21 antipsychotic-naïve FEP patients and 15 healthy controls. Characteristics of the temporal trajectories between whole-brain functional connectivity meta-states were examined via resting-state functional MRI using elements of network science. We compared the cohorts of cases and controls and explored their differences as well as potential associations with symptoms, cognition, and antipsychotic medication doses. STUDY RESULTS: We found that the temporal sequence in which patients' brain dynamics visited the different states was more redundant and segregated. Patients were less flexible than controls in changing their network in time from different configurations, and explored the whole landscape of possible states in a less efficient way. These changes were related to the dose of antipsychotics the patients were receiving. We replicated the relationship with antipsychotic medication in the antipsychotic-naïve FEP sample scanned before and after treatment. CONCLUSIONS: We conclude that psychosis is related to a temporal disorganization of the brain's dynamic functional connectivity, and this is associated with antipsychotic medication use.

Structural brain abnormalities in schizophrenia in adverse environments: examining the effect of poverty and violence in six Latin American cities.

BACKGROUND: Social and environmental factors such as poverty or violence modulate the risk and course of schizophrenia. However, how they affect the brain in patients with psychosis remains unclear. AIMS: We studied how environmental factors are related to brain structure in patients with schizophrenia and controls in Latin America, where these factors are large and unequally distributed. METHOD: This is a multicentre study of magnetic resonance imaging in patients with schizophrenia and controls from six Latin American cities. Total and voxel-level grey matter volumes, and their relationship with neighbourhood characteristics such as average income and homicide rates, were analysed with a general linear model. RESULTS: A total of 334 patients with schizophrenia and 262 controls were included. Income was differentially related to total grey matter volume in both groups (P = 0.006). Controls showed a positive correlation between total grey matter volume and income (R = 0.14, P = 0.02). Surprisingly, this relationship was not present in patients with schizophrenia (R = -0.076, P = 0.17). Voxel-level analysis confirmed that this interaction was widespread across the cortex. After adjusting for global brain changes, income was positively related to prefrontal cortex volumes only in controls. Conversely, the hippocampus in patients with schizophrenia, but not in controls, was relatively larger in affluent environments. There was no significant correlation between environmental violence and brain structure. CONCLUSIONS: Our results highlight the interplay between environment, particularly poverty, and individual characteristics in psychosis. This is particularly important for harsh environments such as low- and middle-income countries, where potentially less brain vulnerability (less grey matter loss) is sufficient to become unwell in adverse (poor) environments.

Transitions between human functional brain networks reveal complex, cost-efficient and behaviorally-relevant temporal paths.

Resting-state functional MRI activity is organized as a complex network. However, this coordinated brain activity changes with time, raising questions about its evolving temporal arrangement. Does the brain visit different configurations through time in a random or ordered way? Advances in this area depend on developing novel paradigms that would allow us to shed light on these issues. We here propose to study the temporal changes in the functional connectome by looking at transition graphs of network activity. Nodes of these graphs correspond to brief whole-brain connectivity patterns (or meta-states), and directed links to the temporal transition between consecutive meta-states. We applied this method to two datasets of healthy subjects (160 subjects and a replication sample of 54), and found that transition networks had several non-trivial properties, such as a heavy-tailed degree distribution, high clustering, and a modular organization. This organization was implemented at a low biological cost with a high cost-efficiency of the dynamics. Furthermore, characteristics of the subjects' transition graphs, including global efficiency, local efficiency and their transition cost, were correlated with cognition and motor functioning. All these results were replicated in both datasets. We conclude that time-varying functional connectivity patterns of the brain in health progress in time in a highly organized and complex order, which is related to behavior.

Effectiveness of Sleep Deprivation in Treating Acute Bipolar Depression as Augmentation Strategy: A Systematic Review and Meta-Analysis.

BACKGROUND: Bipolar disorder is a disabling disease characterized by the recurrence of mood episodes. Successful strategies for the acute treatment of bipolar depression are still a matter of controversy. Total sleep deprivation (TSD) has shown acute antidepressant effect; however, the prompt relapse of depressive symptoms after sleep recovery has been reported. Taking this into consideration, we aimed to address a twofold research question: what are the acute effects of adding TSD to pharmacological treatment and what are the acute and chronic effects of adding medications to TSD. METHODS: MEDLINE, Embase, Cochrane Central Register of Controlled Trials, and ClinicalTrials.gov databases were searched for clinical trials assessing bipolar depression and TSD. Two independent reviewers selected and classified 90 abstracts. The outcomes we assessed were change in Hamilton Depression Rating Scale (HDRS) or Montgomery-Asberg Depression Rating Scale (MADRS), sustained long-term response rate, treatment-emergent mania or hypomania, and tolerability (using dropout rates as a proxy). The compared groups were: TSD alone versus TSD plus medications and medications alone versus medications plus TSD. Data was analyzed using Stata 16.0. RESULTS: Patients treated with TSD plus medications compared with medications alone showed a significant decrease in depressive symptomatology after one week (SMD -0.584 [95% CI -1.126 to -0.042], p = 0.03. Also, a significant decrease in depressive symptomatology (SMD -0.894 [95% CI -1.388 to -0.399], p < 0.001) was found in the group with TSD plus medications compared with TSD alone, at the 10th day of treatment. We meta-analyzed the long-term effect of the TSD. It showed a sustained antidepressant effect (log OR = 2.365 (95% CI 0.95 to 3.779, p < 0.001) in the group where TSD was combined with medication when compared with patients treated only with TSD. Finally, no differences in tolerability (log OR = 0.234 (95% CI -1.164 to 1.632, p = 0.74) or affective switch were found. CONCLUSION: Adding TSD to medications to bipolar depression treatment resulted in an augmentation in acute response. We also found that medications have a positive impact in acute response when added to TSD. Furthermore, this higher response rate was maintained after 3 months while keeping Lithium therapy.

Author Correction: Subgenual anterior cingulate cortex controls sadness-induced modulations of cognitive and emotional network hubs.

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has not been fixed in the paper.

Subgenual anterior cingulate cortex controls sadness-induced modulations of cognitive and emotional network hubs.

The regulation of cognitive and emotional processes is critical for proper executive functions and social behavior, but its specific mechanisms remain unknown. Here, we addressed this issue by studying with functional magnetic resonance imaging the changes in network topology that underlie competitive interactions between emotional and cognitive networks in healthy participants. Our behavioral paradigm contrasted periods with high emotional and cognitive demands by including a sadness provocation task followed by a spatial working memory task. The sharp contrast between successive tasks was designed to enhance the separability of emotional and cognitive networks and reveal areas that regulate the flow of information between them (hubs). By applying graph analysis methods on functional connectivity between 20 regions of interest in 22 participants we identified two main brain network modules, one dorsal and one ventral, and their hub areas: the left dorsolateral prefrontal cortex (dlPFC) and the left medial frontal pole (mFP). These hub areas did not modulate their mutual functional connectivity following sadness but they did so through an interposed area, the subgenual anterior cingulate cortex (sACC). Our results identify dlPFC and mFP as areas regulating interactions between emotional and cognitive networks, and suggest that their modulation by sadness experience is mediated by sACC.

A Computational Model of Major Depression: the Role of Glutamate Dysfunction on Cingulo-Frontal Network Dynamics.

Major depression disease (MDD) is associated with the dysfunction of multinode brain networks. However, converging evidence implicates the reciprocal interaction between midline limbic regions (typified by the ventral anterior cingulate cortex, vACC) and the dorso-lateral prefrontal cortex (dlPFC), reflecting interactions between emotions and cognition. Furthermore, growing evidence suggests a role for abnormal glutamate metabolism in the vACC, while serotonergic treatments (selective serotonin reuptake inhibitor, SSRI) effective for many patients implicate the serotonin system. Currently, no mechanistic framework describes how network dynamics, glutamate, and serotonin interact to explain MDD symptoms and treatments. Here, we built a biophysical computational model of 2 areas (vACC and dlPFC) that can switch between emotional and cognitive processing. MDD networks were simulated by slowing glutamate decay in vACC and demonstrated sustained vACC activation. This hyperactivity was not suppressed by concurrent dlPFC activation and interfered with expected dlPFC responses to cognitive signals, mimicking cognitive dysfunction seen in MDD. Simulation of clinical treatments (SSRI or deep brain stimulation) counteracted this aberrant vACC activity. Theta and beta/gamma oscillations correlated with network function, representing markers of switch-like operation in the network. The model shows how glutamate dysregulation can cause aberrant brain dynamics, respond to treatments, and be reflected in EEG rhythms as biomarkers of MDD.