Predictors of functional outcome in patients with major depression and bipolar disorder: A dynamic network approach to identify distinct patterns of interacting symptoms.

The purpose of this study is to use a dynamic network approach as an innovative way to identify distinct patterns of interacting symptoms in patients with Major Depressive Disorder (MDD) and patients with Bipolar Type I Disorder (BD). More precisely, the hypothesis will be testing that the phenotype of patients is driven by disease specific connectivity and interdependencies among various domains of functioning even in the presence of underlying common mechanisms. In a prospective observational cohort study, hundred-forty-three patients were recruited at the Psychiatric Clinic "Villa dei Gerani" (Catania, Italy), 87 patients with MDD and 56 with BD with a depressive episode. Two nested sub-groups were treated for a twelve-week period, which allowed us to explore differences in the pattern of symptom distribution (central vs. peripheral) and their connectedness (strong vs weak) before (T0) and after (T1) treatment. All patients underwent a complete neuropsychological evaluation at baseline (T0) and at T1. A network structure was computed for MDD and BD patients at T0 and T1 from a covariance matrix of 17 items belonging to three domains-neurocognitive, psychosocial, and mood-related (affective) to identify what symptoms were driving the networks. Clinically relevant differences were observed between MDD and BD, at T0 and after 12 weeks of pharmacological treatment. At time T0, MDD patients displayed an affective domain strongly connected with the nodes of psychosocial functioning, while direct connectivity of the affective domain with the neurocognitive cluster was absent. The network of patients with BD, in contrast, revealed a cluster of highly interconnected psychosocial nodes but was guided by neurocognitive functions. The nodes related to the affective domain in MDD are less connected and placed in the periphery of the networks, whereas in BD they are more connected with psychosocial and neurocognitive nodes. Noteworthy is that, from T0 to T1 the "Betweenness" centrality measure was lower in both disorders which means that fewer "shortest paths" between nodes pass through the affective domain. Moreover, fewer edges were connected directly with the nodes in this domain. In MDD patients, pharmacological treatment primarily affected executive functions which seem to improve with treatment. In contrast, in patients with BD, treatment resulted in improvement of overall connectivity and centrality of the affective domain, which seems then to affect and direct the overall network. Though different network structures were observed for MDD and BD patients, data suggest that treatment should include tailored cognitive therapy, because improvement in this central domain appeared to be fundamental for better outcomes in other domains. In sum, the advantage of network analysis is that it helps to predict the trajectory of future phenotype related disease manifestations. In turn, this allows new insights in how to balance therapeutic interventions, involving different fields of function and combining pharmacological and non-pharmacological treatment modalities.

Moderate support for the use of digital tracking to support climate-mitigation strategies.

The use of digital tracking of individuals throughout the coronavirus 2019 (COVID-19) pandemic renewed societal debates on the efficacy and ethics of digital surveillance to mitigate collective crises. While digital emissions tracking is being used to support climate-mitigation strategies, to date there has been limited exploration of the opportunities and challenges of deploying it at the individual level. Here, we assess temporal and regional differences in levels of support for the use of digital surveillance in times of crisis, such as climate change. Results from a global survey indicate moderate support for the use of digital tracking, including for personal carbon footprints. Response varied regionally, with the lowest support in North America and Europe. This study raises key questions-if digital surveillance tools could be part of a socially acceptable response to the climate crisis, is it worth exploring? Or is this an unacceptable risk for society?

Clinical and Neurocognitive Predictors of Functional Outcome in Depressed Patients with Partial Response to Treatment: One Year Follow-Up Study.

BACKGROUND: Cognitive dysfunction represents a distinct biological and clinical dimension in major depression disorders (MDD) and cognitive performance strongly affects psychosocial functioning in patients diagnosed with MDD. OBJECTIVE: To assess which neurocognitive variables at baseline predict the functional outcome of MDD patients in a 1-year follow-up study as assessed by Functioning Assessment Short Test (FAST) and whether the improvement observed on affective and cognitive symptoms in our 12 week-prospective observational study after treatment with selective serotonin reuptake inhibitors (SSRIs) and selective noradrenalin reuptake inhibitors (SNRIs) can affect the following long-term psychosocial functional outcome at 1 year in the same MDD patients. METHODS: We recruited a total of 31 patients (8 males; 23 females) with MDD who had previously completed a pharmacological treatment with SSRIs (n = 22) or SNRIs (n = 9) for 12 weeks, and then continued the same pharmacological treatment for 1 year. After an average 1-year follow-up, they were interviewed with the FAST to assess functional outcome. Multivariate analyses were applied to identify clinical and neurocognitive predictors of functional outcome. RESULTS: Total Montreal Cognitive Assessment (MoCA), Digit Span forward (Span F) and backward (Span B), and 15 Rey words immediate recall (Rey I) scores significantly correlated with FAST. However, after performing regression models only Rey immediate recall score was useful to predict long-term functional outcome (Pearson correlation coefficient R= -0.68, p < 0.001) in four specific subdomains of FAST. When considering changes in affective and cognitive symptoms at the end of the 12 weeks of pharmacological treatment with SSRI or SNRIs (T1-T0) by multiple regression analysis, we found that Span F-test predicted scores in the FAST leisure domain, whereas, changes in Span F, Frontal Assessment Battery (FAB) and Rey I predicted psychosocial functioning in the specific "cognitive" subdomains of FAST. CONCLUSION: Our data suggest that long-term psychosocial functioning can be influenced by neurocognitive performance at baseline, with verbal memory playing a key role in overall functioning. Furthermore, improvement in verbal memory can predict functional outcome at one year in MDD patients with a recent history of partial response to antidepressants.

Selective Serotonin Reuptake Inhibitors and Serotonin and Noradrenaline Reuptake Inhibitors Improve Cognitive Function in Partial Responders Depressed Patients: Results from a Prospective Observational Cohort Study.

BACKGROUND: Major Depressive disorder (MDD) is often accompanied by cognitive deficits, involving attention, learning, memory and executive functioning. Selective Serotonin Reuptake Inhibitors (SSRIs) and Serotonin and Noradrenaline Reuptake Inhibitors (SNRIs) show efficacy on affective symptoms, but it is unclear whether or not they improve cognitive symptoms. METHODS: We carried out a 12 week-prospective observational study in two cohorts of recurrent moderate-severe partial responder MDD patients, to test the hypothesis that SSRIs and/or SNRIs may affect cognitive symptoms and assess whether or not such an effect was correlated to their effect on affective symptoms. All patients underwent cognitive and neuropsychiatric assessment at baseline, 4- and 12-week follow-up. Thirty-three patients in the SSRI- and sixteen patients in the SNRI-cohort completed the follow-up. RESULTS: Both SSRIs and SNRIs reduced affective symptoms and improved global cognitive function. Both SSRIs and SNRIs improved executive function and verbal memory. Global cognitive function, verbal memory and executive function improved both in full and partial responder patients. Finally, there was no correlation between baseline Mini Mental State Examination, Montreal Cognitive Assessment and Frontal Assessment Battery scores and the mean change in Hamilton Psychiatric Rating scale for Depression or Beck Depression Inventory at the end of the 12 weeks of treatment. CONCLUSION: Present data show that SSRIs and SNRIs improve cognitive symptoms in MDD independently from their efficacy on affective symptoms. Affective and cognitive symptoms may represent distinct psychopathological dimensions of MDD with different response to antidepressant drugs.