Dataset Information

Bipolar polygenic loading and bipolar spectrum features in major depressive disorder.

ABSTRACT: Family and genetic studies indicate overlapping liability for major depressive disorder and bipolar disorder. The purpose of the present study was to determine whether this shared genetic liability influences clinical presentation.A polygenic risk score for bipolar disorder, derived from a large genome-wide association meta-analysis, was generated for each subject of European-American ancestry (n = 1,274) in the Sequential Treatment Alternatives to Relieve Depression study (STAR*D) outpatient major depressive disorder cohort. A hypothesis-driven approach was used to test for association between bipolar disorder risk score and features of depression associated with bipolar disorder in the literature. Follow-up analyses were performed in two additional cohorts.A generalized linear mixed model including seven features hypothesized to be associated with bipolar spectrum illness was significantly associated with bipolar polygenic risk score [F = 2.07, degrees of freedom (df) = 7, p = 0.04]. Features included early onset, suicide attempt, recurrent depression, atypical depression, subclinical mania, subclinical psychosis, and severity. Post-hoc univariate analyses demonstrated that the major contributors to this omnibus association were onset of illness at age ? 18 years [odds ratio (OR) = 1.2, p = 0.003], history of suicide attempt (OR = 1.21, p = 0.03), and presence of at least one manic symptom (OR = 1.16, p = 0.02). The maximal variance in these traits explained by polygenic score ranged from 0.8% to 1.1%. However, analyses in two replication cohorts testing a five-feature model did not support this association.Bipolar genetic loading appeared to be associated with bipolar-like presentation in major depressive disorder in the primary analysis. However, the results were at most inconclusive because of lack of replication. Replication efforts were challenged by different ascertainment and assessment strategies in the different cohorts. The methodological approach described here may prove useful in applying genetic data to clarify psychiatric nosology in future studies.

SUBMITTER: Wiste A

PROVIDER: S-EPMC4427243 | biostudies-literature | 2014 Sep

REPOSITORIES: biostudies-literature

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Bipolar polygenic loading and bipolar spectrum features in major depressive disorder.

Wiste Anna A Robinson Elise B EB Milaneschi Yuri Y Meier Sandra S Ripke Stephan S Clements Caitlin C CC Fitzmaurice Garrett M GM Rietschel Marcella M Penninx Brenda W BW Smoller Jordan W JW Perlis Roy H RH

Bipolar disorders 20140412 6

<h4>Objectives</h4>Family and genetic studies indicate overlapping liability for major depressive disorder and bipolar disorder. The purpose of the present study was to determine whether this shared genetic liability influences clinical presentation.<h4>Methods</h4>A polygenic risk score for bipolar disorder, derived from a large genome-wide association meta-analysis, was generated for each subject of European-American ancestry (n = 1,274) in the Sequential Treatment Alternatives to Relieve Depr ...[more]

PMID: 24725193

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Project description:ContextIt has been suggested that patients with major depressive disorder (MDD) who display pretreatment features suggestive of bipolar disorder or bipolar spectrum features might have poorer treatment outcomes.ObjectiveTo assess the association between bipolar spectrum features and antidepressant treatment outcome in MDD.DesignOpen treatment followed by sequential randomized controlled trials.SettingPrimary and specialty psychiatric outpatient centers in the United States.ParticipantsMale and female outpatients aged 18 to 75 years with a DSM-IV diagnosis of nonpsychotic MDD who participated in the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) study.InterventionsOpen treatment with citalopram followed by up to 3 sequential next-step treatments.Main outcome measuresNumber of treatment levels required to reach protocol-defined remission, as well as failure to return for the postbaseline visit, loss to follow-up, and psychiatric adverse events. For this secondary analysis, putative bipolar spectrum features, including items on the mania and psychosis subscales of the Psychiatric Diagnosis Screening Questionnaire, were examined for association with treatment outcomes.ResultsOf the 4041 subjects who entered the study, 1198 (30.0%) endorsed at least 1 item on the psychosis scale and 1524 (38.1%) described at least 1 recent maniclike/hypomaniclike symptom. Irritability and psychoticlike symptoms at entry were significantly associated with poorer outcomes across up to 4 treatment levels, as were shorter episodes and some neurovegetative symptoms of depression. However, other indicators of bipolar diathesis including recent maniclike symptoms and family history of bipolar disorder as well as summary measures of bipolar spectrum features were not associated with treatment resistance.ConclusionSelf-reported psychoticlike symptoms were common in a community sample of outpatients with MDD and strongly associated with poorer outcomes. Overall, the data do not support the hypothesis that unrecognized bipolar spectrum illness contributes substantially to antidepressant treatment resistance.

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.

Dataset Information

Bipolar polygenic loading and bipolar spectrum features in major depressive disorder.

Publications

Bipolar polygenic loading and bipolar spectrum features in major depressive disorder.

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