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

Abstract

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.

A network study to differentiate suicide attempt risk profiles in male and female patients with major depressive disorder

“…The network analysis conducted on the whole sample (Figure 1, left side) showed that in patients with MDD, there is a separation between the neurocognitive and psychosocial domains (Platania et al, 2023). The latter also includes the two nodes assessing depression: HDRS (Node 7) and BDI‐II (Node 8).…”

“…Focusing on diagnostic protocols, it is interesting to note that HDRS seems to correlate better (Table 2) with the presence of ‘suicide attempts’ when compared to the BDI‐II. This finding can be explained in various ways: several studies demonstrate that HDRS seems to be a psychometric tool more sensitive for MDD, while BDI‐II is a more efficient assessment tool for bipolar depression (Carneiro et al, 2015; Guerrera et al, 2023; Hunt et al, 2003; Platania et al, 2023; Rush et al, 1986). This is due to both the different markers of the pathologies and the uneven subjective experience felt by patients, differently represented by the tests (Platania et al, 2020).…”

Impact of Stress during COVID-19 Pandemic in Italy: A Study on Dispositional and Behavioral Dimensions for Supporting Evidence-Based Targeted Strategies

“…These data are in agreement with previous scientific evidence. In fact, with the pandemic’s progression, students and females showed greater levels of stress, depression, and anxiety that needed specific interventions for cognitive, affective, and psychosocial symptoms [ 46 , 47 , 48 ]. It should also be noted that our investigation highlighted a significant sex difference regarding stress levels, while in the validation study of the M.S.P.…”

Combining Mini-Mental State Examination and Montreal Cognitive Assessment for assessing the clinical efficacy of cholinesterase inhibitors in mild Alzheimer’s disease: a pilot study

“…For instance, the Montreal Cognitive Assessment (MoCA) [ 4 ] is a global measure of cognition that has shown high sensitivity and specificity in detecting Mild Cognitive Impairment (MCI), while other specific cognitive domains and neuropsychiatric symptoms should be considered to give clearer a picture into person’s intrinsic capacity [ 5 ], in particular executive functions [ 6 ] and affective symptoms such as depression [ 7 ].…”