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Understanding Aging in Bipolar Disorder by Integrating Archival Clinical Research Datasets.

ABSTRACT: OBJECTIVE:Although 25% of people with bipolar disorder (BD) are over age 60, there is a dearth of research on older age bipolar disorder (OABD). This report describes an initial effort to create an integrated OABD database using the U.S. National Institute of Mental Health Data Archive (NDA). Goals were to: 1) combine data from three BD studies in the United States that included overlapping data elements; 2) investigate research questions related to aims of the original studies; and 3) take an important first step toward combining existing datasets relevant to aging and BD. METHODS:Data were prepared and uploaded to the NDA, with a focus on data elements common to all studies. As appropriate, data were harmonized to select or collapse categories suitable for cross-walk analysis. Associations between age, BD symptoms, functioning, medication load, medication adherence, and medical comorbidities were assessed. The total sample comprised 451 individuals, mean age 57.7 (standard deviation: 13.1) years. RESULTS:Medical comorbidity was not significantly associated with either age or functioning and there did not appear to be an association between medication load, comorbidity, age, and adherence. Men and African-Americans were significantly more likely to have poor adherence. Both BD mania and depression symptoms were associated with functioning, but this differed across studies. CONCLUSION:Despite limitations including heterogeneity in study design and samples and cross-sectional methodology, integrated datasets represent an opportunity to better understand how aging may impact the presentation and evolution of chronic mental health disorders across the lifespan.

SUBMITTER: Eyler LT

PROVIDER: S-EPMC6739177 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature

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Project description:Background and Objectives: Depressive symptoms are prominent in both major depressive disorder (MDD) and bipolar disorder (BD). However, comparative research on the network structure of depressive symptoms in these two diagnostic groups has been limited. This study aims to compare the network structure of depressive symptoms in MDD and BD, providing a deeper understanding of the depressive symptomatology of each disorder. Materials and Methods: The Zung Self-Rating Depressive Scale, a 20-item questionnaire, was administered to assess the depressive symptoms in individuals with MDD (n = 322) and BD (n = 516). A network analysis was conducted using exploratory graph analysis (EGA), and the network structure was analyzed using regularized partial correlation models. To validate the dimensionality of the Zung SDS, principal component analysis (PCA) was adopted. Centrality measures of the depressive symptoms within each group were assessed, followed by a network comparison test between the two groups. Results: In both diagnostic groups, the network analysis revealed four distinct categories, aligning closely with the PCA results. "Depressed affect" emerged as the most central symptom in both MDD and BD. Furthermore, non-core symptoms, "Personal devaluation" in MDD and "Confusion" in BD, displayed strong centrality. The network comparison test did not reveal significant differences in the network structure between MDD and BD. Conclusions: The absence of significant differences in the network structures between MDD and BD suggests that the underlying mechanisms of depressive symptoms may be similar across these disorders. The identified central symptoms, including "Depressed affect", in both disorders and the distinct non-core symptoms in each highlight the complexity of the depressive symptomatology. Future research should focus on validating these symptoms as therapeutic targets and incorporate various methodologies, including non-metric dimension reduction techniques or canonical analysis.

Project description:Background: A mild pro-inflammatory status accompanies bipolar disorder (BD). Inflammation can cause a shift in monoamine metabolism, thereby activating more cytotoxic pathways. The extent to which low-grade inflammation in BD interacts with monoamine metabolism and how this accords to aging and clinical course is unknown. Objectives: We evaluated the presence of alterations in inflammation and monoamine metabolism in BD throughout different mood states and the role of aging therein. Methods: Sixty-seven patients with BD were included during an acute mood episode, either depressive (n = 29), (hypo)manic (n = 29), or mixed (n = 9). Plasma levels of inflammatory markers [tumor necrosis factor alpha (TNF-α), interferon gamma (IFN-y), interleukin-6 (IL-6), and C-reactive protein (CRP)] and markers of monoamine metabolism (neopterin, tryptophan, kynurenine, phenylalanine, and tyrosine) were measured repeatedly during a follow-up of 8 months. Levels in patients were compared to controls (n = 35) and correlated to HDRS-17 and YMRS scores. Spearman correlations and linear mixed model analysis were used for statistical analysis. Results: Forty-nine patients and 30 controls (age range: 22-62 years) completed the study. No significant differences in inflammatory markers were found between patients and controls overall. Tryptophan, tyrosine, and phenylalanine levels were lower in patients. In both patients and controls, markers of inflammation correlated only weakly with markers of monoamine metabolism, but correlations representative for activity of cytotoxic pathways in monoamine metabolism were more pronounced in patients. In patients, but not in controls, older age was associated with increases in inflammatory markers (IL-6, CRP, neopterin) and the kynurenine/tryptophan ratio. None of the biological markers correlated significantly with mood symptom severity. Conclusion: Our data suggest an increased susceptibility of patients with BD to develop a pro-inflammatory state and to shift monoamine metabolism toward more cytotoxic pathways. These findings are in support of the theory of neuroprogression and accelerated aging in BD. Since associations between biological markers and clinical characteristics are limited, it remains to be determined if alterations in biological markers are due to a disease effect or rather are a consequence of confounding factors.

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Understanding Aging in Bipolar Disorder by Integrating Archival Clinical Research Datasets.

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